[ { "path": ".clang-format", "content": "Language: Cpp # Maybe change\nStandard: Auto # Maybe change\nBasedOnStyle: Google # Maybe change\nAlignAfterOpenBracket: BlockIndent # Better overview\nAlignArrayOfStructures: Right # Better overview (but might make editing harder)\nAlignConsecutiveAssignments: true # Better overview (but might make editing harder)\nAlignConsecutiveBitFields: true # Better overview (but might make editing harder)\nAlignConsecutiveDeclarations: false # Better Overview, as otherwise we would separate a identifier from its type\nAlignEscapedNewlines: Left # Better Overview\nAlignOperands: AlignAfterOperator # Better overview\nAlignTrailingComments:\n Kind: Always # Better overview\nAllowAllArgumentsOnNextLine: false # Better overview\nAllowAllParametersOfDeclarationOnNextLine: false # Better overview\nAllowShortBlocksOnASingleLine: Empty # Better overview\nAllowShortCaseLabelsOnASingleLine: false # Better overview\nAllowShortEnumsOnASingleLine: false # Better overview\nAllowShortFunctionsOnASingleLine: Empty # Better overview\nAllowShortIfStatementsOnASingleLine: Never # Better overview\nAllowShortLambdasOnASingleLine: Empty # Better overview\nAllowShortLoopsOnASingleLine: false # Better overview\nAlwaysBreakAfterReturnType: None # Don't produce an unnecessary empty line\nAlwaysBreakBeforeMultilineStrings: true # Better overview\nAlwaysBreakTemplateDeclarations: Yes # Better overview\nBinPackArguments: false # Better overview\nBinPackParameters: false # Better overview\nBitFieldColonSpacing: Both # Better overview\nBraceWrapping:\n AfterCaseLabel: false # Don't produce an unnecessary empty line\n AfterClass: false # Don't produce an unnecessary empty line\n AfterControlStatement: Never # Don't produce an unnecessary empty line\n AfterEnum: false # Don't produce an unnecessary empty line\n AfterFunction: false # Don't produce an unnecessary empty line\n AfterNamespace: false # Don't produce an unnecessary empty line\n AfterObjCDeclaration: false # Don't produce an unnecessary empty line\n AfterStruct: false # Don't produce an unnecessary empty line\n AfterUnion: false # Don't produce an unnecessary empty line\n AfterExternBlock: false # Don't produce an unnecessary empty line\n BeforeCatch: false # Don't produce an unnecessary empty line\n BeforeElse: false # Don't produce an unnecessary empty line\n BeforeLambdaBody: false # Don't produce an unnecessary empty line\n BeforeWhile: false # Don't produce an unnecessary empty line\n IndentBraces: false # Don't produce an unnecessary empty line\n SplitEmptyFunction: false # Don't produce an unnecessary empty line\n SplitEmptyRecord: false # Don't produce an unnecessary empty line\n SplitEmptyNamespace: false # Don't produce an unnecessary empty line\nBreakAfterAttributes: Never # Don't produce an unnecessary empty line\nBreakBeforeBinaryOperators: NonAssignment # Allows easier out-commenting of single parts of assignments\nBreakBeforeBraces: Attach # Don't produce an unnecessary empty line\nBreakBeforeConceptDeclarations: true # Better overview\nBreakBeforeTernaryOperators: true # Better overview\nBreakConstructorInitializers: BeforeComma # Better overview and easier out-commenting of single initializers\nBreakInheritanceList: BeforeComma # Better overview and easier out-commenting of base classes\nBreakStringLiterals: false # Avoid config-based wrapping of strings (as it actually depends on the users screen size how wrapping should be applied)\nColumnLimit: 1000 # No limit (use high number to enforce removal of existing breaks); Avoid config-based wrapping of strings (as it actually depends on the users screen size how wrapping should be applied)\nCompactNamespaces: false # Better overview\nCpp11BracedListStyle: true # Better overview\nDeriveLineEnding: false # Formatting should be fixed, not derived\nDerivePointerAlignment: false # Formatting should be fixed, not derived\nEmptyLineAfterAccessModifier: Never # Don't produce an unnecessary empty line\nEmptyLineBeforeAccessModifier: Always # Here empty lines help overview, as they clearly make the current access modifier more visible\nFixNamespaceComments: true # Better overview\nIncludeBlocks: Regroup # Better overview\nIndentAccessModifiers: false # As members will be intended, this separates access modifiers from members more clearly\nIndentCaseBlocks: false # We don't wrap braces here, so intend would move closing brace out of vertical line\nIndentCaseLabels: true # Better overview, as it's visible, that case is inside switch\nIndentExternBlock: Indent # Better overview\nIndentGotoLabels: true # Better overview, as otherwise e.gt breaks would break out intendation\nIndentPPDirectives: AfterHash # Better overview, as hash tag still marks post processing, but the directives are intended\nIndentRequiresClause: false #Intend would break statement out of vertical line\nIndentWidth: 4 # Make tab indentation work\nIndentWrappedFunctionNames: true # Better overview, as the breaking of function name is marked\nInsertBraces: false # Done by clang-tidy #Better overview and maintaining of code, as additional statements can be easily added. WARNING: May break code. Better directly avoid clauses without braces\nKeepEmptyLinesAtTheStartOfBlocks: false # Remove an unnecessary empty line\nLambdaBodyIndentation: Signature # Better overview\nNamespaceIndentation: Inner # Avoid having most of the code intended if we have a big namespace\nPackConstructorInitializers: Never # Better overview\nPointerAlignment: Left # Better overview, as star is part of the type\nQualifierAlignment: Leave # clang-format is not able to handle this without breaking code\nReferenceAlignment: Left # Better overview, as ampersand is part of the type\nReflowComments: false # I don't know, what clang-format is doing here, but it looks bad: Avoid config-based wrapping of strings (as it actually depends on the users screen size how wrapping should be applied)\nRequiresClausePosition: OwnLine # Better overview\nRequiresExpressionIndentation: OuterScope # Better overview\nSeparateDefinitionBlocks: Leave # Allow user to specify that on his own. May be used to group some blocks together that belong together, while separating other blocks\nShortNamespaceLines: 0 # Better overview, as namespaces are clearly marked by closing comment and opening statement\nSortIncludes: CaseSensitive # Better overview. TODO: Maybe change that if it causes problems\nSortUsingDeclarations: true # Better overview. TODO: Maybe change that if it causes problems\nSpaceAfterCStyleCast: true # Better overview\nSpaceAfterLogicalNot: false # Avoid unnecessary space, cause actually the unary operator belongs to the identifier\nSpaceAfterTemplateKeyword: false # Space would separate template from it's parameters\nSpaceAroundPointerQualifiers: Default # Don't known why we should change this. TODO: Reevaluate?\nSpaceBeforeAssignmentOperators: true # Better overview, as we separate identifier from operator\nSpaceBeforeCaseColon: false # Avoid unnecessary space\nSpaceBeforeCpp11BracedList: true # Better overview\nSpaceBeforeCtorInitializerColon: true # Better overview, as we mark more clearly, where initializer list starts\nSpaceBeforeInheritanceColon: true # Better overview, as we mark more clearly, where base class list starts\nSpaceBeforeParens: Never # Avoid unnecessary space\nSpaceBeforeRangeBasedForLoopColon: false # Avoid unnecessary space\nSpaceBeforeSquareBrackets: false # Avoid unnecessary space\nSpaceInEmptyBlock: false # Avoid unnecessary space\nSpaceInEmptyParentheses: false # Avoid unnecessary space\nSpacesBeforeTrailingComments: 0 # Avoid unnecessary space\nSpacesInAngles: Never # Avoid unnecessary space\nSpacesInCStyleCastParentheses: false # Avoid unnecessary space\nSpacesInConditionalStatement: false # Avoid unnecessary space\nSpacesInParentheses: false # Avoid unnecessary space\nSpacesInSquareBrackets: false # Avoid unnecessary space\nTabWidth: 4 # Make tab indentation work\nUseCRLF: true # Better compatibility\nUseTab: Always # Use tabs where we can" }, { "path": ".clang-tidy", "content": "# abseil-cleanup-ctad Avoid doubled printing of type\n# abseil-duration-addition Ensure explicit use of correct duration type\n# abseil-duration-comparison Ensure explicit use of correct duration type\n# abseil-duration-conversion-cast Ensure correct cast of durations\n# abseil-duration-division Ensure explicit use of correct duration division\n# abseil-duration-factory-float Avoid use of inperformant conversion funnctions\n# abseil-duration-factory-scale Avoid use of wrong scale conversion funnctions\n# abseil-duration-subtraction Ensure explicit use of correct duration type\n# abseil-duration-unnecessary-conversion Avoid unnecessary conversion\n# abseil-faster-strsplit-delimiter Avoid inperformant use of Strings when Characters are suggested\n#xabseil-no-internal-dependencies Not used, cause use of internal details is probably intended when found\n#xabseil-no-namespace Not used, cause use of namespace is probably intended when found\n# abseil-redundant-strcat-calls Avoid unnecessary function calls\n# abseil-str-cat-append Avoid concatination when appending is suggested\n# abseil-string-find-startswith Ensure std::string::startsWith is called instead of find-functions\n#xabseil-string-find-str-contains Not used, cause it suggests usage of abseil functions instead of standard library functions\n# abseil-time-comparison Ensure explicit use of time type when comnparing times\n# abseil-time-subtraction Ensure explicit use of time type\n#xabseil-upgrade-duration-conversions Not used, as it suggests possibly unwanted casts, which te compiler already warns us about\n#xaltera-id-dependent-backward-branch Not used, cause it did report at every loop # Avoid inperformant design of loops\n# altera-kernel-name-restriction Avoid usage of files named similiar to internal API files\n# altera-single-work-item-barrier Avoid unnecessary use of barriers\n#xaltera-struct-pack-align Not used, cause we don't want allignment messages for structs nnot used in OpenCL kernels\n#xaltera-unroll-loops Not used, cause it does not understand expression based unrolls and reports for all code, even code not in kernels\n# boost-use-to-string Ensure use of standard library functions where possible\n# bugprone-argument-comment Ensure correct use of argument names in comments\n# bugprone-assert-side-effect Avoid assertions with side-effects\n# bugprone-assignment-in-if-condition Avoid assignments in if-conditions\n# bugprone-bad-signal-to-kill-thread Avoid SIGTERM when attempting to kill a thread\n# bugprone-bool-pointer-implicit-conversion Avoid implicit conversion from pointer to bool\n# bugprone-branch-clone Avoid identical branches\n# bugprone-copy-constructor-init Avoid wrong usage of copy constructors\n# bugprone-dangling-handle Avoid dangling references\n# bugprone-dynamic-static-initializers Avoid dynamic initialization of static variables in possibly shared context\n#xbugprone-easily-swappable-parameters Not used, cause it would require refactoring of API\n#xbugprone-exception-escape Not used, cause it reported escape were non could take place # Avoid throwing of exceptions where it is not allowed\n# bugprone-fold-init-type Ensure explicit use of correct type in fold functions\n# bugprone-forward-declaration-namespace Avoid forward declarations in wrong namespace\n# bugprone-forwarding-reference-overload Avoid use of perfect forwarding constructor where use of copy or move constructor is suggested\n# bugprone-implicit-widening-of-multiplication-result Avoid unintended overflow on multiplication\n# bugprone-inaccurate-erase Ensure correct use of erase functions\n# bugprone-incorrect-roundings Avoid incorrect rounding of values\n# bugprone-infinite-loop Avoid infinite loops\n# bugprone-integer-division Avoid integer division in floating-point context\n# bugprone-lambda-function-name Avoid printing the name of an unnamed function\n# bugprone-macro-parentheses Avoid macros that rely on possibly misleading usage of parenthesis\n#xbugprone-macro-repeated-side-effects Not used, cause I don't know what it does\n# bugprone-misplaced-operator-in-strlen-in-alloc Avoid probably unintended addition to strings\n# bugprone-misplaced-pointer-arithmetic-in-alloc Avoid probably unintended addition to pointers\n# bugprone-misplaced-widening-cast Avoid loss of precision by misplaced casts\n# bugprone-move-forwarding-reference Ensure forwarding references are forwared not moved\n# bugprone-multiple-statement-macro Avoid statements from falling out an conditioned block when inserting macros. (NOTE: Should not happen if ifs without braces are avoided)\n# bugprone-no-escape Ensure pointers marked as noescape do not escape from their scope\n# bugprone-not-null-terminated-result Avoid strings, that are not null-terminated\n# bugprone-parent-virtual-call Avoid calls of inherited virtual functions when a call to non-virtual function is suggested\n# bugprone-posix-return Ensure posix fuinctions returning non-negatiove only do not return negative values\n# bugprone-redundant-branch-condition Avoid nested if-statements with the same condition a parent has.\n# bugprone-reserved-identifier Avoid usage of reserved names\n# bugprone-shared-ptr-array-mismatch Avoid wrong initializationj of shared pointers with arrays\n# bugprone-signal-handler Ensure correct behaviour of signal handlers\n# bugprone-signed-char-misuse Ensure correct conversion from signed char to bigger signed integer types\n# bugprone-sizeof-container Avoid use of sizeof where use of .size() is suggested\n# bugprone-sizeof-expression Avoid use of sizeof where it is not suggested\n# bugprone-spuriously-wake-up-functionsp Avoid missed spurious wakeup\n# bugprone-standalone-empty Avoid use of .empty() where use of .clear() is suggested\n# bugprone-string-constructor Avoid misuse of string constructors\n# bugprone-string-integer-assignment Avoid assignments of integers to strings\n# bugprone-string-literal-with-embedded-nul Avoid unintended use of escaped NUL characters in strings\n# bugprone-stringview-nullptr Avoid string views of null-pointers\n# bugprone-suspicious-enum-usage Avoid misuse of enums as integers where not suggested\n# bugprone-suspicious-include Avoid inclusion of implementation files\n# bugprone-suspicious-memory-comparison Avoid memory comparison where it seems to be not suggested\n# bugprone-suspicious-memset-usage Avoid usage of memset in a way probably not suggested\n# bugprone-suspicious-missing-comma Avoid possibly missing commata\n# bugprone-suspicious-realloc-usage Ensure that memory does not get lost on failure of realloc\n# bugprone-suspicious-semicolon Avoid semicolon where it is probably not intended\n# bugprone-suspicious-string-compare Avoid wrong comparison of the result of a string comparison\n# bugprone-swapped-arguments Avoid possibly swapped arguments on function calls\n# bugprone-terminating-continue Avoid continue from being executed in every loop iteration, skipping parts of the loop body\n# bugprone-throw-keyword-missing Ensure throw-keyword is used when exception might be thrown\n# bugprone-too-small-loop-variable Ensure loop variables have a type big enough for the loops range\n# bugprone-unchecked-optional-access Avoid unsafe access to optionals\n# bugprone-undefined-memory-manipulation Avoid undefined manipulation of memory\n# bugprone-undelegated-constructor Ensure delegated constructors are correctly called\n# bugprone-unhandled-exception-at-new Ensure exception is handled on call of new, if not passed to parent function\n#xbugprone-unhandled-self-assignment Not used, cause it reported even if the special case was handled # Avoid data loss on self assignment\n# bugprone-unsafe-functions Ensure safe functions are used where available\n# bugprone-unused-raii Avoid use of RAII where it is not suggested\n# bugprone-unused-return-value Avoid unused return values\n# bugprone-use-after-move Avoid usage of an object after it was moved\n# bugprone-virtual-near-miss Avoid unintended misname of virtual functions in derived classes\n# cert-dcl50-cpp Avoid c-style variadic functions\n#xcert-dcl58-cpp Not used, cause use of namespace is probably intended when found\n# cert-err34-c Avoid unchecked use of string to integer conversion functions\n# cert-err52-cpp Avoid long jumps\n# cert-err58-cpp Ensure exceptions in constructors at global space are handled\n# cert-err60-cpp Ensure throw expressions are nothrow copy constructible\n#xcert-flp30-c Not used, cause floats in for loops are probably intended when encountered\n# cert-mem57-cpp Avoid use of default new operator for over-aligned types\n#xcert-msc50-cpp Not used, cause usage of random number generators is probably intended when encountered\n#xcert-msc51-cpp Not used, cause usage of random number generators is probably intended when encountered\n# cert-oop57-cpp Avoid use of memory manipulation functions where a call to an apropriate class function is suggested\n# cert-oop58-cpp Ensure source object is not modified on copy constructors\n# concurrency-mt-unsafe Avoid parallel calls to non-threadsafe functions\n# concurrency-thread-canceltype-asynchronous Ensure pthreads are cancled safely\n# cppcoreguidelines-avoid-capture-default-when-capturing-this Avoid misleading captures in lambda functions\n# cppcoreguidelines-avoid-capturing-lambda-coroutines Avoid use of already freed variables in asynchronous lambdas\n# cppcoreguidelines-avoid-const-or-ref-data-members Ensure const accessors are used instead of const members\n#xcppcoreguidelines-avoid-do-while Not used, cause do-while loops can also increase readability in some scenarios\n# cppcoreguidelines-avoid-goto Avoid use of goto\n# cppcoreguidelines-avoid-non-const-global-variables Avoid global variables, that are not const\n# cppcoreguidelines-avoid-reference-coroutine-parameters Avoid dangling references by coroutines\n#xcppcoreguidelines-init-variables Not used, cause it marked valid assignments and compiler already does such checks\n# cppcoreguidelines-interfaces-global-init Avoid some order-of-initialization problems\n# cppcoreguidelines-macro-usage Avoid usage of macros where modern language structures are suggested\n# cppcoreguidelines-narrowing-conversions Avoid silent narrwoing\n# cppcoreguidelines-no-malloc Avoid usage of c allocation where modern language structures are suggested\n#xcppcoreguidelines-owning-memory Not used, cause we don't use gsl\n#xcppcoreguidelines-prefer-member-initializer Not used, cause initialization should happen at constructor.\n# cppcoreguidelines-pro-bounds-array-to-pointer-decay Avoid usage of pointers as arrays\n#xcppcoreguidelines-pro-bounds-constant-array-index Not used, cause it did not detect in fact constant ranges (like for loops with constant upper bound) # Avoid out-of-bounds for static arrays\n# cppcoreguidelines-pro-bounds-pointer-arithmetic Avoid usage of pointer-arithmetic\n# cppcoreguidelines-pro-type-const-cast Avoid modification of const values\n# cppcoreguidelines-pro-type-cstyle-cast Avoid unsafe casts\n# cppcoreguidelines-pro-type-member-init Ensure class members are initialized\n# cppcoreguidelines-pro-type-reinterpret-cast Avoid unsafe casts\n# cppcoreguidelines-pro-type-static-cast-downcast Avoid use of static_cast where dynamic_cast is suggested\n# cppcoreguidelines-pro-type-union-access Avoid use of unions (NOTE: Some compilers may explicitly allow the use of unions as type prunning)\n# cppcoreguidelines-pro-type-vararg Avoid c-style variadic functions\n# cppcoreguidelines-rvalue-reference-param-not-moved Ensure rvalue parameters are moved into a function\n# cppcoreguidelines-slicing Avoid copying a derived instance into a base instance\n# cppcoreguidelines-special-member-functions Ensure that all special members/constructors are defined\n# cppcoreguidelines-virtual-class-destructor Ensure correct definition of virtual destructors\n# darwin-avoid-spinlock Avoid use of deprecated locks\n# darwin-dispatch-once-nonstatic Avoid undefined behaviour when dispatching\n#xfuchsia-default-arguments-calls Not used, cause default arguments are intended to be used\n#xfuchsia-default-arguments-declarations Not used, cause default arguments are intended to be used\n#xfuchsia-multiple-inheritance Not used, cause multi inheritance is probably intended when encountered\n#xfuchsia-overloaded-operator Not used, cause operator overloading is intended to be used\n#xfuchsia-statically-constructed-objects Not used, cause already handled by other checks in a less restricting way\n#xfuchsia-trailing-return Not used, cause I'm not sure what it does\n#xfuchsia-virtual-inheritance Not used, cause virtual inheritance is probably intended when encountered\n# google-build-explicit-make-pair Ensure correct types are used in make_pair\n# google-build-namespaces Avoid anonymous namespaces in headers\n# google-build-using-namespace Ensure explicit use of namespaces\n#xgoogle-default-arguments Not used, cause default arguments are intended to be used\n# google-explicit-constructor Avoid unintended implicit conversion\n# google-global-names-in-headers Avoid excessive use of namespaces in headers\n#xgoogle-readability-avoid-underscore-in-googletest-name Not used, cause naming of tests is up to the user\n# google-readability-casting Avoid use of c-style casts\n#xgoogle-readability-todo Not used, cause TODOs might often be used without assignment to bug numbers or users\n#xgoogle-runtime-int Not used, cause platform-specific integer size may be intended\n#xgoogle-runtime-operator Not used, cause operator overloading is intended to be used\n# google-upgrade-googletest-case Avoid use of deprecated functions\n# hicpp-exception-baseclass Ensure only exceptions are thrown\n# hicpp-multiway-paths-covered Ensure explicit covering of all branches\n# hicpp-no-assembler Avoid inline assembly\n#xhicpp-signed-bitwise Not used, cause it is fixed or will be fixed in c++20 # Avoid undefined behaviour at bitwise operations on signed integers\n#xllvm-header-guard Not used, cause it does not take care of root directory, generating very weird header guards\n#xllvm-include-order Not used, cause different include order style might be wanted by user (see .clang-format)\n# llvm-namespace-comment Ensure namespace end comment for long namespaces\n#xlvm-prefer-isa-or-dyn-cast-in-conditionals Not used, cause use of different casts might be intended\n#xllvm-prefer-register-over-unsigned Not used, cause I don't know where this applies\n#xllvm-twine-local Not used, cause I don't know where this applies\n#xllvmlibc-callee-namespace Not used, cause I don't know where this applies\n#xllvmlibc-implementation-in-namespace Not used, cause I don't know where this applies\n#xllvmlibc-inline-function-decl Not used, cause user might not use LLVM for compilation\n#xllvmlibc-restrict-system-libc-headers Not used, cause user might not use LLVM for compilation\n# misc-confusable-identifiers Avoid confusable identifiers\n#xmisc-const-correctness Not used, cause id produced false-positives # Ensure const is used where suggested\n# misc-definitions-in-headers Avoid not inlined definitions in headers\n# misc-misleading-bidirectional Avoid misleading characters in code\n# misc-misleading-identifier Avoid misleading characters in code\n# misc-misplaced-const Avoid wrong usage of const caused by typedefs\n# misc-new-delete-overloads Ensure each object-level new got an corresponding delete and the other way round\n# misc-no-recursion Avoid recursion\n# misc-non-copyable-objects Avoid copying types that are not copieable\n#xmisc-non-private-member-variables-in-classes Not used, cause this would blow up code massively\n# misc-redundant-expression Avoid redundant expressions\n# misc-static-assert Avoid use of assert where static_assert is suggested\n# misc-throw-by-value-catch-by-reference Ensure exceptions are catched by reference and thrown by value\n# misc-unconventional-assign-operator Ensure assignment operators are correctly defined\n# misc-uniqueptr-reset-release Ensure unique_ptr are moved on assignment\n# misc-unused-alias-decls Avoid unused namespaces aliases\n# misc-unused-parameters Avoid unused parameters\n# misc-unused-using-decls Avoid unused usings\n# misc-use-anonymous-namespace Ensure anonymouse namespaces are preferred before static global scope\n# modernize-avoid-bind Avoid binding of functions where lambdas can be used\n# modernize-avoid-c-arrays Avoid use of c-style arrays where std::array can be used\n#xmodernize-concat-nested-namespaces Not used, as namespaces might be extended, later requiring rewriting\n# modernize-deprecated-headers Avoid deprecated headers\n# modernize-deprecated-ios-base-aliases Avoid deprecated namespace\n#xmodernize-loop-convert Not used, cause range-based for might be bugprone and not usable in some situations\n# modernize-macro-to-enum Avoid use of macros, where enums are suggested\n#xmodernize-make-shared Not used, cause both does have pros and cons\n#xmodernize-make-unique Not used, cause both does have pros and cons\n# modernize-pass-by-value Avoid inefficient pass-by-reference\n#xmodernize-raw-string-literal Not used, cause raw strings are confusing when mixed with non-raw strings\n# modernize-redundant-void-arg Avoid use of void arg\n# modernize-replace-auto-ptr Avoid use of deprecated type\n# modernize-replace-disallow-copy-and-assign-macro Avoid deprecated macro\n# modernize-replace-random-shuffle Avoid use of deprecated function\n#xmodernize-return-braced-init-list Not used, cause array initializers hide explicite function calls, making it less clear what happens\n# modernize-shrink-to-fit Ensure shrink_to_fit is used where suggested\n# modernize-type-traits Ensure type_traits short functions are used\n# modernize-unary-static-assert Avoid use of empty string static_assert\n#xmodernize-use-auto Not used, cause auto hides type information\n# modernize-use-bool-literals Avoid assigning integers to bools\n#xmodernize-use-default-member-init Not used, cause initialization should happen at constructor.\n# modernize-use-emplace Ensure emplace functions are used where suggested\n# modernize-use-equals-default Ensure default constructor is explicitly defined where suggested\n# modernize-use-equals-delete Ensure constructor is explicitly deleted where suggested\n# modernize-use-nodiscard Ensure nodiscard is used where suggested\n# modernize-use-noexcept Ensure noexcept is used where suggested\n# modernize-use-nullptr Avoid use of NULL, instead use nullptr\n# modernize-use-override Ensure override is used where suggested\n#xmodernize-use-trailing-return-type Not used, cause it blows up code\n#xmodernize-use-transparent-functors Not used, as the removed type information is probably relevant\n# modernize-use-uncaught-exceptions Avoid usage of deprecated type\n#xmodernize-use-using Not used, cause typedef has clear syntax and clear use, while using has not\n# mpi-buffer-deref Avoid passing double pointers to mpi functions where single pointers are suggested\n# mpi-type-mismatch Ensure correct type buffer is passed to mpi function\n# openmp-exception-escape Ensure OpenMP blocks are well-bracketed\n# openmp-use-default-none Ensure explicit declaration of data sharing type\n# performance-faster-string-find Avoid call to find with a string literall where a call with a character is suggested\n# performance-for-range-copy Avoid copying values in ranged for loops where use by reference is suggested\n# performance-implicit-conversion-in-loop Avoid implicit conversion in ranged for loops\n# performance-inefficient-algorithm Avoid inefficient usage of container functiosn where more efficient implementations exist\n# performance-inefficient-string-concatenation Avoid addition of strings where appending is suggested\n# performance-inefficient-vector-operation Avoid inefficient calls to std::vector functions where it could be acceletarted\n# performance-move-const-arg Avoid move where none is suggested\n# performance-move-constructor-init Avoid move construictor where copy constructor is suggested in initialization of base classes\n# performance-no-automatic-move Avoid const where it prevents moving\n# performance-no-int-to-ptr Avoid casts between integer and pointer\n# performance-noexcept-move-constructor Ensure move constructors are marked with noexcept\n# performance-trivially-destructible Avoid making a function non-trivial destructible when it should be possible\n# performance-type-promotion-in-math-fn Ensure math float functions are explicitly called\n# performance-unnecessary-copy-initialization Avoid copy initialization where initialization by const reference is suggested\n# performance-unnecessary-value-param Avoid pass-by-value where pass-by-reference is suggested\n# portability-simd-intrinsics Avoid use of SIMD builtins where standard library (experimental) function is suggested\n# portability-std-allocator-const Avoid use of containers of const types\n#xreadability-avoid-const-params-in-decls Not used, cause it may be intended to match declaration and definition\n# readability-avoid-unconditional-preprocessor-if Avoid preprocessor ifs always evaluation to zrue/false\n# readability-braces-around-statements Avoid conditionals and loops without braces, as they are bad readable, bugprone and bat maintainable\n# readability-const-return-type Avoid const in return types, improving compiler optimizations\n# readability-container-contains Avoid usage of find() and count() where use of contains() is suggested\n# readability-container-data-pointer Ensure data() is used where available\n# readability-container-size-empty Avoid usage of size() where use of empty() is suggested\n# readability-convert-member-functions-to-static Ensure members are declared static when they actually are static\n# readability-delete-null-pointer Avoid checks for nullptr where it is unnecessary\n# readability-duplicate-include Avoid duplicate includes\n#xreadability-else-after-return Not used, cause explicit usage of branches might highlight branch covering\n#xreadability-function-cognitive-complexity Not used, cause no easy fis is suggested\n#xreadability-function-size Not used, cause no easy fis is suggested\n#xreadability-identifier-length Not used, cause no easy fis is suggested\n# readability-identifier-naming Ensure consistent naming of identifiers\n# readability-implicit-bool-conversion Avoid implicit conversion of bool\n# readability-inconsistent-declaration-parameter-name Ensure names of parameters in definition match name of parametersin declaration\n# readability-isolate-declaration Avoid declaring several variables in one statement\n# readability-magic-numbers Avoid magic numbers\n#xreadability-make-member-function-const Not used, cause is produces wrong results (mark functions const that have non-const access to members) # Ensure constant member functions are declared const\n# readability-misleading-indentatione Ensure intendation is consistent\n# readability-misplaced-array-index Avoid misused array index\n# readability-named-parameter Ensure parameters are named\n#xreadability-non-const-parameter Not used, cause is produces wrong results (mark parameters const that are have non-const accessed) # Ensure the use constant pointers where suggested\n# readability-operators-representation Avoid mixed tokens for operators\n# readability-qualified-auto Ensure auto pointers are declared as pointers\n# readability-redundant-access-specifiers Avoid dooubling of access specifiers\n# readability-redundant-control-flow Avoid unnecessary return or continue\n# readability-redundant-declaration Avoid redundant declarations\n# readability-redundant-function-ptr-dereference Avoid doubled dereferencing of functions where single dereference is suggested\n# readability-redundant-member-init Avoid unnecessary member initialization\n# readability-redundant-preprocessor Avoid redundant preprocessors\n# readability-redundant-smartptr-get Avoid doubled dereferencing of smart pointers where single dereference is suggested\n# readability-redundant-string-cstr Avoid calls to c_str where it is not necessary\n# readability-redundant-string-init Avoid unnecessary string initialization\n# readability-simplify-boolean-expr Avoid complex boolean expressions when simple ones are suggested\n# readability-simplify-subscript-expr Avoid call to data() where it is not necessary\n# readability-static-accessed-through-instance Avoid access of static members through instances\n# readability-static-definition-in-anonymous-namespace Avoid unnecessary static in anonymous namespace\n# readability-string-compare Ensure string compare function is used where suggested\n#xreadability-suspicious-call-argument Not used as too heuristic\n# readability-uniqueptr-delete-release Avoid complex deletion of unique pointers\n#xreadability-uppercase-literal-suffix Not used, cause lower case is completely valid\n# readability-use-anyofallof Avoid use of ranged for loop where special function is suggested\nChecks: >\n abseil-cleanup-ctad\n ,abseil-duration-addition\n ,abseil-duration-comparison\n ,abseil-duration-conversion-cast\n ,abseil-duration-division\n ,abseil-duration-factory-float\n ,abseil-duration-factory-scale\n ,abseil-duration-subtraction\n ,abseil-duration-unnecessary-conversion\n ,abseil-faster-strsplit-delimiter\n ,abseil-redundant-strcat-calls\n ,abseil-str-cat-append\n ,abseil-string-find-startswith\n ,abseil-time-comparison\n ,abseil-time-subtraction\n ,altera-kernel-name-restriction\n ,altera-single-work-item-barrier\n ,boost-use-to-string\n ,bugprone-argument-comment\n ,bugprone-assert-side-effect\n ,bugprone-assignment-in-if-condition\n ,bugprone-bad-signal-to-kill-thread\n ,bugprone-bool-pointer-implicit-conversion\n ,bugprone-branch-clone\n ,bugprone-copy-constructor-init\n ,bugprone-dangling-handle\n ,bugprone-dynamic-static-initializers\n ,bugprone-fold-init-type\n ,bugprone-forward-declaration-namespace\n ,bugprone-forwarding-reference-overload\n ,bugprone-implicit-widening-of-multiplication-result\n ,bugprone-inaccurate-erase\n ,bugprone-incorrect-roundings\n ,bugprone-infinite-loop\n ,bugprone-integer-division\n ,bugprone-lambda-function-name\n ,bugprone-macro-parentheses\n ,bugprone-misplaced-operator-in-strlen-in-alloc\n ,bugprone-misplaced-pointer-arithmetic-in-alloc\n ,bugprone-misplaced-widening-cast\n ,bugprone-move-forwarding-reference\n ,bugprone-multiple-statement-macro\n ,bugprone-no-escape\n ,bugprone-not-null-terminated-result\n ,bugprone-parent-virtual-call\n ,bugprone-posix-return\n ,bugprone-redundant-branch-condition\n ,bugprone-reserved-identifier\n ,bugprone-shared-ptr-array-mismatch\n ,bugprone-signal-handler\n ,bugprone-signed-char-misuse\n ,bugprone-sizeof-container\n ,bugprone-sizeof-expression\n ,bugprone-spuriously-wake-up-functions\n ,bugprone-standalone-empty\n ,bugprone-string-constructor\n ,bugprone-string-integer-assignment\n ,bugprone-string-literal-with-embedded-nul\n ,bugprone-stringview-nullptr\n ,bugprone-suspicious-enum-usage\n ,bugprone-suspicious-include\n ,bugprone-suspicious-memory-comparison\n ,bugprone-suspicious-memset-usage\n ,bugprone-suspicious-missing-comma\n ,bugprone-suspicious-realloc-usage\n ,bugprone-suspicious-semicolon\n ,bugprone-suspicious-string-compare\n ,bugprone-swapped-arguments\n ,bugprone-terminating-continue\n ,bugprone-throw-keyword-missing\n ,bugprone-too-small-loop-variable\n ,bugprone-unchecked-optional-access\n ,bugprone-undefined-memory-manipulation\n ,bugprone-undelegated-constructor\n ,bugprone-unhandled-exception-at-new\n ,bugprone-unsafe-functions\n ,bugprone-unused-raii\n ,bugprone-unused-return-value\n ,bugprone-use-after-move\n ,bugprone-virtual-near-miss\n ,cert-dcl50-cpp\n ,cert-err34-c\n ,cert-err52-cpp\n ,cert-err58-cpp\n ,cert-err60-cpp\n ,cert-mem57-cpp\n ,cert-oop57-cpp\n ,cert-oop58-cpp\n ,concurrency-mt-unsafe\n ,concurrency-thread-canceltype-asynchronous\n ,cppcoreguidelines-avoid-capture-default-when-capturing-this\n ,cppcoreguidelines-avoid-capturing-lambda-coroutines\n ,cppcoreguidelines-avoid-const-or-ref-data-members\n ,cppcoreguidelines-avoid-goto\n ,cppcoreguidelines-avoid-non-const-global-variables\n ,cppcoreguidelines-avoid-reference-coroutine-parameters\n ,cppcoreguidelines-interfaces-global-init\n ,cppcoreguidelines-macro-usage\n ,cppcoreguidelines-narrowing-conversions\n ,cppcoreguidelines-no-malloc\n ,cppcoreguidelines-pro-bounds-array-to-pointer-decay\n ,cppcoreguidelines-pro-bounds-pointer-arithmetic\n ,cppcoreguidelines-pro-type-const-cast\n ,cppcoreguidelines-pro-type-cstyle-cast\n ,cppcoreguidelines-pro-type-member-init\n ,cppcoreguidelines-pro-type-reinterpret-cast\n ,cppcoreguidelines-pro-type-static-cast-downcast\n ,cppcoreguidelines-pro-type-union-access\n ,cppcoreguidelines-pro-type-vararg\n ,cppcoreguidelines-rvalue-reference-param-not-moved\n ,cppcoreguidelines-slicing\n ,cppcoreguidelines-special-member-functions\n ,cppcoreguidelines-virtual-class-destructor\n ,darwin-avoid-spinlock\n ,darwin-dispatch-once-nonstatic\n ,google-build-explicit-make-pair\n ,google-build-namespaces\n ,google-build-using-namespace\n ,google-explicit-constructor\n ,google-global-names-in-headers\n ,google-readability-casting\n ,google-upgrade-googletest-case\n ,hicpp-exception-baseclass\n ,hicpp-multiway-paths-covered\n ,hicpp-no-assembler\n ,llvm-namespace-comment\n ,misc-confusable-identifiers\n ,misc-definitions-in-headers\n ,misc-misleading-bidirectional\n ,misc-misleading-identifier\n ,misc-misplaced-const\n ,misc-new-delete-overloads\n ,misc-no-recursion\n ,misc-non-copyable-objects\n ,misc-redundant-expression\n ,misc-static-assert\n ,misc-throw-by-value-catch-by-reference\n ,misc-unconventional-assign-operator\n ,misc-uniqueptr-reset-release\n ,misc-unused-alias-decls\n ,misc-unused-parameters\n ,misc-unused-using-decls\n ,misc-use-anonymous-namespace\n ,modernize-avoid-bind\n ,modernize-avoid-c-arrays\n ,modernize-deprecated-headers\n ,modernize-deprecated-ios-base-aliases\n ,modernize-macro-to-enum\n ,modernize-pass-by-value\n ,modernize-redundant-void-arg\n ,modernize-replace-auto-ptr\n ,modernize-replace-disallow-copy-and-assign-macro\n ,modernize-replace-random-shuffle\n ,modernize-shrink-to-fit\n ,modernize-type-traits\n ,modernize-unary-static-assert\n ,modernize-use-bool-literals\n ,modernize-use-emplace\n ,modernize-use-equals-default\n ,modernize-use-equals-delete\n ,modernize-use-nodiscard\n ,modernize-use-noexcept\n ,modernize-use-nullptr\n ,modernize-use-override\n ,modernize-use-uncaught-exceptions\n ,mpi-buffer-deref\n ,mpi-type-mismatch\n ,openmp-exception-escape\n ,openmp-use-default-none\n ,performance-faster-string-find\n ,performance-for-range-copy\n ,performance-implicit-conversion-in-loop\n ,performance-inefficient-algorithm\n ,performance-inefficient-string-concatenation\n ,performance-inefficient-vector-operation\n ,performance-move-const-arg\n ,performance-move-constructor-init\n ,performance-no-automatic-move\n ,performance-no-int-to-ptr\n ,performance-noexcept-move-constructor\n ,performance-trivially-destructible\n ,performance-type-promotion-in-math-fn\n ,performance-unnecessary-copy-initialization\n ,performance-unnecessary-value-param\n ,portability-simd-intrinsics\n ,portability-std-allocator-const\n ,readability-avoid-unconditional-preprocessor-if\n ,readability-braces-around-statements\n ,readability-const-return-type\n ,readability-container-contains\n ,readability-container-data-pointer\n ,readability-container-size-empty\n ,readability-convert-member-functions-to-static\n ,readability-delete-null-pointer\n ,readability-duplicate-include\n ,readability-identifier-naming\n ,readability-implicit-bool-conversion\n ,readability-inconsistent-declaration-parameter-name\n ,readability-isolate-declaration\n ,readability-magic-numbers\n ,readability-misleading-indentation\n ,readability-misplaced-array-index\n ,readability-named-parameter\n ,readability-operators-representation\n ,readability-qualified-auto\n ,readability-redundant-access-specifiers\n ,readability-redundant-control-flow\n ,readability-redundant-declaration\n ,readability-redundant-function-ptr-dereference\n ,readability-redundant-member-init\n ,readability-redundant-preprocessor\n ,readability-redundant-smartptr-get\n ,readability-redundant-string-cstr\n ,readability-redundant-string-init\n ,readability-simplify-boolean-expr\n ,readability-simplify-subscript-expr\n ,readability-static-accessed-through-instance\n ,readability-static-definition-in-anonymous-namespace\n ,readability-string-compare\n ,readability-uniqueptr-delete-release\n ,readability-use-anyofallof\nCheckOptions:\n - key: bugprone-argument-comment.StrictMode # Must be the exact parameter name\n value: true\n - key: bugprone-misplaced-widening-cast.CheckImplicitCasts # Also check implicit casts\n value: true\n - key: bugprone-sizeof-expression.WarnOnSizeOfIntegerExpression # Warn when fetching sizeof integer value\n value: true\n - key: bugprone-string-constructor.WarnOnLargeLength # Large strings are probably intended when encountered\n value: true\n - key: bugprone-suspicious-enum-usage.StrictMode # Also detect suspicious enums\n value: true\n - key: bugprone-suspicious-missing-comma.SizeThreshold # Detect all occurencies\n value: 0\n - key: bugprone-suspicious-missing-comma.RatioThreshold # Detect all occurencies\n value: 1.0\n - key: bugprone-suspicious-missing-comma.MaxConcatenatedTokens # But not if we got more than x tokens\n value: 5\n - key: bugprone-suspicious-string-compare.WarnOnLogicalNotComparison # Also warn on negation\n value: true\n - key: bugprone-unhandled-self-assignment.WarnOnlyIfThisHasSuspiciousField # Always warn\n value: false\n - key: cppcoreguidelines-narrowing-conversions.WarnWithinTemplateInstantiation # Also warn on template instantiations\n value: true\n - key: cppcoreguidelines-narrowing-conversions.PedanticMode # Also warn when assigned value is exactly representable\n value: true\n - key: cppcoreguidelines-pro-type-member-init.IgnoreArrays # Ignore arrays for performance reason\n value: true\n - key: cppcoreguidelines-pro-type-member-init.UseAssignment # Use assignment, cause bracket initializer hides information about the called function\n value: true\n - key: hicpp-multiway-paths-covered.WarnOnMissingElse # Also warn if else branch is not covered\n value: true\n - key: misc-const-correctness.WarnPointersAsValues # Also warn for pointer values\n value: true\n - key: misc-const-correctness.TransformPointersAsValues # Also transform for pointer values\n value: true\n - key: modernize-avoid-bind.PermissiveParameterList # Avoid errors causd by replacement\n value: true\n - key: performance-for-range-copy.WarnOnAllAutoCopies # Warn when using auto in ranged for loops\n value: true\n - key: performance-inefficient-string-concatenation.StrictMode # Check everywhere\n value: true\n - key: portability-simd-intrinsics.Suggest # Suggest alternatives\n value: true \n - key: readability-identifier-naming.GetConfigPerFile # Use config from where the identifier is defined\n value: true\n - key: readability-inconsistent-declaration-parameter-name.Strict # Parameters must match exactly\n value: true\n - key: readability-magic-numbers.IgnoredIntegerValues # Only accept 0 and 1 (for bitwise operation and as true value=\n value: '1'\n - key: readability-magic-numbers.IgnoredFloatingPointValues # Only accept 0.0 and 1.0 (for 1.0/x)\n value: '1.0'\n - key: readability-magic-numbers.IgnoreTypeAliases # Ignore in type definitions\n value: true\n - key: readability-magic-numbers.IgnoreUserDefinedLiterals # Ignore in literal definitions\n value: true\n - key: readability-redundant-member-init.IgnoreBaseInCopyConstructors # Ignore unnecessary base class initialuization for compiler compatibility\n value: true\n - key: readability-uniqueptr-delete-release.PreferResetCall # Call reset instead of assigning nullptr\n value: true\n \n #Naming conventions\n - key: readability-identifier-naming.AbstractClassCase\n value: CamelCase\n - key: readability-identifier-naming.ClassCase\n value: CamelCase\n - key: readability-identifier-naming.ClassConstantCase\n value: UPPER_CASE\n - key: readability-identifier-naming.ClassMemberCase\n value: lower_case\n - key: readability-identifier-naming.ClassMethodCase\n value: lower_case\n - key: readability-identifier-naming.ConstantCase\n value: lower_case\n - key: readability-identifier-naming.ConstantMemberCase\n value: lower_case\n - key: readability-identifier-naming.ConstantParameterCase\n value: lower_case\n - key: readability-identifier-naming.ConstantPointerParameterCase\n value: lower_case\n - key: readability-identifier-naming.ConstexprMethodCase\n value: lower_case\n - key: readability-identifier-naming.ConstexprVariableCase\n value: UPPER_CASE\n - key: readability-identifier-naming.EnumCase\n value: CamelCase\n - key: readability-identifier-naming.EnumConstantCase\n value: CamelCase\n - key: readability-identifier-naming.FunctionCase\n value: lower_case\n - key: readability-identifier-naming.GlobalConstantCase\n value: UPPER_CASE\n - key: readability-identifier-naming.GlobalConstantPointerCase\n value: UPPER_CASE\n - key: readability-identifier-naming.GlobalFunctionCase\n value: lower_case\n - key: readability-identifier-naming.GlobalPointerCase\n value: lower_case\n - key: readability-identifier-naming.GlobalVariableCase\n value: lower_case\n - key: readability-identifier-naming.InlineNamespaceCase\n value: lower_case\n - key: readability-identifier-naming.LocalConstantCase\n value: lower_case\n - key: readability-identifier-naming.LocalConstantPointerCase\n value: lower_case\n - key: readability-identifier-naming.LocalPointerCase\n value: lower_case\n - key: readability-identifier-naming.LocalVariableCase\n value: lower_case\n - key: readability-identifier-naming.MacroDefinitionCase\n value: UPPER_CASE\n - key: readability-identifier-naming.MemberCase\n value: lower_case\n - key: readability-identifier-naming.MethodCase\n value: lower_case\n - key: readability-identifier-naming.NamespaceCase\n value: lower_case\n - key: readability-identifier-naming.ParameterCase\n value: lower_case\n - key: readability-identifier-naming.ParameterPackCase\n value: lower_case\n - key: readability-identifier-naming.PointerParameterCase\n value: lower_case\n - key: readability-identifier-naming.PrivateMemberCase\n value: lower_case\n - key: readability-identifier-naming.PrivateMethodCase\n value: lower_case\n - key: readability-identifier-naming.ProtectedMemberCase\n value: lower_case\n - key: readability-identifier-naming.ProtectedMethodCase\n value: lower_case\n - key: readability-identifier-naming.PublicMemberCase\n value: lower_case\n - key: readability-identifier-naming.PublicMethodCase\n value: lower_case\n - key: readability-identifier-naming.ScopedEnumConstantCase\n value: UPPER_CASE\n - key: readability-identifier-naming.StaticConstantCase\n value: UPPER_CASE\n - key: readability-identifier-naming.StaticVariableCase\n value: lower_case\n - key: readability-identifier-naming.StructCase\n value: CamelCase\n - key: readability-identifier-naming.TemplateParameterCase\n value: CamelCase\n - key: readability-identifier-naming.TemplateTemplateParameterCase\n value: CamelCase\n - key: readability-identifier-naming.TypeTemplateParameterCase\n value: CamelCase\n - key: readability-identifier-naming.UnionCase\n value: CamelCase\n - key: readability-identifier-naming.ValueTemplateParameterCase\n value: CamelCase\n - key: readability-identifier-naming.VariableCase\n value: lower_case\n - key: readability-identifier-naming.VirtualMethodCase\n value: CamelCase\nFormatStyle: file # Use .clang-format for formatting\nHeaderFileExtensions: ['h', 'hh', 'hpp', 'hxx', 'cuh'] # All headers, including CUDA headers\nImplementationFileExtensions: ['c', 'cc', 'cpp', 'cxx', 'cu'] # All implementations, including CUDA implementations\nInheritParentConfig: true # Inherit parent config if available\n#SystemHeaders: false # Ignore system headers\nUseColor: true # Use colors if available\nWarningsAsErrors: true # Treat all warnings as errors" }, { "path": ".gitignore", "content": ".vscode\nbuild\nclang-format-all.bat\nclang-tidy-all.bat\nfix_compilation_database.py\n**/*.so\n**/*.exe.manifest\n**/*.exe\n**/*.bgeo\n" }, { "path": ".gitmodules", "content": "[submodule \"Data\"]\n\tpath = Data\n\turl = https://github.com/littlemine/Data.git\n" }, { "path": "CMake/DownloadProject.CMakeLists.cmake.in", "content": "cmake_minimum_required(VERSION 2.8.2)\n\nproject(${DL_ARGS_PROJ}-download NONE)\n\ninclude(ExternalProject)\nExternalProject_Add(${DL_ARGS_PROJ}-download\n ${DL_ARGS_UNPARSED_ARGUMENTS}\n SOURCE_DIR \"${DL_ARGS_SOURCE_DIR}\"\n BINARY_DIR \"${DL_ARGS_BINARY_DIR}\"\n CONFIGURE_COMMAND \"\"\n BUILD_COMMAND \"\"\n INSTALL_COMMAND \"\"\n TEST_COMMAND \"\"\n)\n" }, { "path": "CMake/DownloadProject.LICENSE", "content": "The MIT License (MIT)\n\nCopyright (c) 2015 Crascit\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n\n" }, { "path": "CMake/DownloadProject.cmake", "content": "# MODULE: DownloadProject\n#\n# PROVIDES:\n# download_project( PROJ projectName\n# [PREFIX prefixDir]\n# [DOWNLOAD_DIR downloadDir]\n# [SOURCE_DIR srcDir]\n# [BINARY_DIR binDir]\n# [QUIET]\n# ...\n# )\n#\n# Provides the ability to download and unpack a tarball, zip file, git repository,\n# etc. at configure time (i.e. when the cmake command is run). How the downloaded\n# and unpacked contents are used is up to the caller, but the motivating case is\n# to download source code which can then be included directly in the build with\n# add_subdirectory() after the call to download_project(). Source and build\n# directories are set up with this in mind.\n#\n# The PROJ argument is required. The projectName value will be used to construct\n# the following variables upon exit (obviously replace projectName with its actual\n# value):\n#\n# projectName_SOURCE_DIR\n# projectName_BINARY_DIR\n#\n# The SOURCE_DIR and BINARY_DIR arguments are optional and would not typically\n# need to be provided. They can be specified if you want the downloaded source\n# and build directories to be located in a specific place. The contents of\n# projectName_SOURCE_DIR and projectName_BINARY_DIR will be populated with the\n# locations used whether you provide SOURCE_DIR/BINARY_DIR or not.\n#\n# The DOWNLOAD_DIR argument does not normally need to be set. It controls the\n# location of the temporary CMake build used to perform the download.\n#\n# The PREFIX argument can be provided to change the base location of the default\n# values of DOWNLOAD_DIR, SOURCE_DIR and BINARY_DIR. If all of those three arguments\n# are provided, then PREFIX will have no effect. The default value for PREFIX is\n# CMAKE_BINARY_DIR.\n#\n# The QUIET option can be given if you do not want to show the output associated\n# with downloading the specified project.\n#\n# In addition to the above, any other options are passed through unmodified to\n# ExternalProject_Add() to perform the actual download, patch and update steps.\n# The following ExternalProject_Add() options are explicitly prohibited (they\n# are reserved for use by the download_project() command):\n#\n# CONFIGURE_COMMAND\n# BUILD_COMMAND\n# INSTALL_COMMAND\n# TEST_COMMAND\n#\n# Only those ExternalProject_Add() arguments which relate to downloading, patching\n# and updating of the project sources are intended to be used. Also note that at\n# least one set of download-related arguments are required.\n#\n# If using CMake 3.2 or later, the UPDATE_DISCONNECTED option can be used to\n# prevent a check at the remote end for changes every time CMake is run\n# after the first successful download. See the documentation of the ExternalProject\n# module for more information. It is likely you will want to use this option if it\n# is available to you.\n#\n# EXAMPLE USAGE:\n#\n# include(download_project.cmake)\n# download_project(PROJ googletest\n# GIT_REPOSITORY https://github.com/google/googletest.git\n# GIT_TAG master\n# UPDATE_DISCONNECTED 1\n# QUIET\n# )\n#\n# add_subdirectory(${googletest_SOURCE_DIR} ${googletest_BINARY_DIR})\n#\n#========================================================================================\n\n\nset(_DownloadProjectDir \"${CMAKE_CURRENT_LIST_DIR}\")\n\ninclude(CMakeParseArguments)\n\nfunction(download_project)\n\n set(options QUIET)\n set(oneValueArgs\n PROJ\n PREFIX\n DOWNLOAD_DIR\n SOURCE_DIR\n BINARY_DIR\n # Prevent the following from being passed through\n CONFIGURE_COMMAND\n BUILD_COMMAND\n INSTALL_COMMAND\n TEST_COMMAND\n )\n set(multiValueArgs \"\")\n\n cmake_parse_arguments(DL_ARGS \"${options}\" \"${oneValueArgs}\" \"${multiValueArgs}\" ${ARGN})\n\n # Hide output if requested\n if (DL_ARGS_QUIET)\n set(OUTPUT_QUIET \"OUTPUT_QUIET\")\n else()\n unset(OUTPUT_QUIET)\n message(STATUS \"Downloading/updating ${DL_ARGS_PROJ}\")\n endif()\n\n # Set up where we will put our temporary CMakeLists.txt file and also\n # the base point below which the default source and binary dirs will be\n if (NOT DL_ARGS_PREFIX)\n set(DL_ARGS_PREFIX \"${CMAKE_BINARY_DIR}\")\n endif()\n if (NOT DL_ARGS_DOWNLOAD_DIR)\n set(DL_ARGS_DOWNLOAD_DIR \"${DL_ARGS_PREFIX}/${DL_ARGS_PROJ}-download\")\n endif()\n\n # Ensure the caller can know where to find the source and build directories\n if (NOT DL_ARGS_SOURCE_DIR)\n set(DL_ARGS_SOURCE_DIR \"${DL_ARGS_PREFIX}/${DL_ARGS_PROJ}-src\")\n endif()\n if (NOT DL_ARGS_BINARY_DIR)\n set(DL_ARGS_BINARY_DIR \"${DL_ARGS_PREFIX}/${DL_ARGS_PROJ}-build\")\n endif()\n set(${DL_ARGS_PROJ}_SOURCE_DIR \"${DL_ARGS_SOURCE_DIR}\" PARENT_SCOPE)\n set(${DL_ARGS_PROJ}_BINARY_DIR \"${DL_ARGS_BINARY_DIR}\" PARENT_SCOPE)\n\n # Create and build a separate CMake project to carry out the download.\n # If we've already previously done these steps, they will not cause\n # anything to be updated, so extra rebuilds of the project won't occur.\n configure_file(\"${_DownloadProjectDir}/DownloadProject.CMakeLists.cmake.in\"\n \"${DL_ARGS_DOWNLOAD_DIR}/CMakeLists.txt\")\n execute_process(COMMAND ${CMAKE_COMMAND} -G \"${CMAKE_GENERATOR}\" .\n ${OUTPUT_QUIET}\n WORKING_DIRECTORY \"${DL_ARGS_DOWNLOAD_DIR}\"\n )\n execute_process(COMMAND ${CMAKE_COMMAND} --build .\n ${OUTPUT_QUIET}\n WORKING_DIRECTORY \"${DL_ARGS_DOWNLOAD_DIR}\"\n )\n\nendfunction()\n" }, { "path": "CMake/FindWayland.cmake", "content": "# Try to find Wayland on a Unix system\n#\n# This will define:\n#\n# WAYLAND_FOUND - True if Wayland is found\n# WAYLAND_LIBRARIES - Link these to use Wayland\n# WAYLAND_INCLUDE_DIR - Include directory for Wayland\n# WAYLAND_DEFINITIONS - Compiler flags for using Wayland\n#\n# In addition the following more fine grained variables will be defined:\n#\n# WAYLAND_CLIENT_FOUND WAYLAND_CLIENT_INCLUDE_DIR WAYLAND_CLIENT_LIBRARIES\n# WAYLAND_SERVER_FOUND WAYLAND_SERVER_INCLUDE_DIR WAYLAND_SERVER_LIBRARIES\n# WAYLAND_EGL_FOUND WAYLAND_EGL_INCLUDE_DIR WAYLAND_EGL_LIBRARIES\n#\n# Copyright (c) 2013 Martin Gräßlin \n#\n# Redistribution and use is allowed according to the terms of the BSD license.\n# For details see the accompanying COPYING-CMAKE-SCRIPTS file.\n\nIF (NOT WIN32)\n IF (WAYLAND_INCLUDE_DIR AND WAYLAND_LIBRARIES)\n # In the cache already\n SET(WAYLAND_FIND_QUIETLY TRUE)\n ENDIF ()\n\n # Use pkg-config to get the directories and then use these values\n # in the FIND_PATH() and FIND_LIBRARY() calls\n FIND_PACKAGE(PkgConfig)\n PKG_CHECK_MODULES(PKG_WAYLAND QUIET wayland-client wayland-server wayland-egl wayland-cursor)\n\n SET(WAYLAND_DEFINITIONS ${PKG_WAYLAND_CFLAGS})\n\n FIND_PATH(WAYLAND_CLIENT_INCLUDE_DIR NAMES wayland-client.h HINTS ${PKG_WAYLAND_INCLUDE_DIRS})\n FIND_PATH(WAYLAND_SERVER_INCLUDE_DIR NAMES wayland-server.h HINTS ${PKG_WAYLAND_INCLUDE_DIRS})\n FIND_PATH(WAYLAND_EGL_INCLUDE_DIR NAMES wayland-egl.h HINTS ${PKG_WAYLAND_INCLUDE_DIRS})\n FIND_PATH(WAYLAND_CURSOR_INCLUDE_DIR NAMES wayland-cursor.h HINTS ${PKG_WAYLAND_INCLUDE_DIRS})\n\n FIND_LIBRARY(WAYLAND_CLIENT_LIBRARIES NAMES wayland-client HINTS ${PKG_WAYLAND_LIBRARY_DIRS})\n FIND_LIBRARY(WAYLAND_SERVER_LIBRARIES NAMES wayland-server HINTS ${PKG_WAYLAND_LIBRARY_DIRS})\n FIND_LIBRARY(WAYLAND_EGL_LIBRARIES NAMES wayland-egl HINTS ${PKG_WAYLAND_LIBRARY_DIRS})\n FIND_LIBRARY(WAYLAND_CURSOR_LIBRARIES NAMES wayland-cursor HINTS ${PKG_WAYLAND_LIBRARY_DIRS})\n\n set(WAYLAND_INCLUDE_DIR ${WAYLAND_CLIENT_INCLUDE_DIR} ${WAYLAND_SERVER_INCLUDE_DIR} ${WAYLAND_EGL_INCLUDE_DIR} ${WAYLAND_CURSOR_INCLUDE_DIR})\n\n set(WAYLAND_LIBRARIES ${WAYLAND_CLIENT_LIBRARIES} ${WAYLAND_SERVER_LIBRARIES} ${WAYLAND_EGL_LIBRARIES} ${WAYLAND_CURSOR_LIBRARIES})\n\n list(REMOVE_DUPLICATES WAYLAND_INCLUDE_DIR)\n\n include(FindPackageHandleStandardArgs)\n\n FIND_PACKAGE_HANDLE_STANDARD_ARGS(WAYLAND_CLIENT DEFAULT_MSG WAYLAND_CLIENT_LIBRARIES WAYLAND_CLIENT_INCLUDE_DIR)\n FIND_PACKAGE_HANDLE_STANDARD_ARGS(WAYLAND_SERVER DEFAULT_MSG WAYLAND_SERVER_LIBRARIES WAYLAND_SERVER_INCLUDE_DIR)\n FIND_PACKAGE_HANDLE_STANDARD_ARGS(WAYLAND_EGL DEFAULT_MSG WAYLAND_EGL_LIBRARIES WAYLAND_EGL_INCLUDE_DIR)\n FIND_PACKAGE_HANDLE_STANDARD_ARGS(WAYLAND_CURSOR DEFAULT_MSG WAYLAND_CURSOR_LIBRARIES WAYLAND_CURSOR_INCLUDE_DIR)\n FIND_PACKAGE_HANDLE_STANDARD_ARGS(WAYLAND DEFAULT_MSG WAYLAND_LIBRARIES WAYLAND_INCLUDE_DIR)\n\n MARK_AS_ADVANCED(\n WAYLAND_INCLUDE_DIR WAYLAND_LIBRARIES\n WAYLAND_CLIENT_INCLUDE_DIR WAYLAND_CLIENT_LIBRARIES\n WAYLAND_SERVER_INCLUDE_DIR WAYLAND_SERVER_LIBRARIES\n WAYLAND_EGL_INCLUDE_DIR WAYLAND_EGL_LIBRARIES\n WAYLAND_CURSOR_INCLUDE_DIR WAYLAND_CURSOR_LIBRARIES\n )\n\nENDIF ()\n" }, { "path": "CMake/FindXCB.cmake", "content": "# - FindXCB\n#\n# Copyright 2015 Valve Coporation\n\nfind_package(PkgConfig)\n\nif(NOT XCB_FIND_COMPONENTS)\n set(XCB_FIND_COMPONENTS xcb)\nendif()\n\ninclude(FindPackageHandleStandardArgs)\nset(XCB_FOUND true)\nset(XCB_INCLUDE_DIRS \"\")\nset(XCB_LIBRARIES \"\")\nforeach(comp ${XCB_FIND_COMPONENTS})\n # component name\n string(TOUPPER ${comp} compname)\n string(REPLACE \"-\" \"_\" compname ${compname})\n # header name\n string(REPLACE \"xcb-\" \"\" headername xcb/${comp}.h)\n # library name\n set(libname ${comp})\n\n pkg_check_modules(PC_${comp} QUIET ${comp})\n\n find_path(${compname}_INCLUDE_DIR NAMES ${headername}\n HINTS\n ${PC_${comp}_INCLUDEDIR}\n ${PC_${comp}_INCLUDE_DIRS}\n )\n\n find_library(${compname}_LIBRARY NAMES ${libname}\n HINTS\n ${PC_${comp}_LIBDIR}\n ${PC_${comp}_LIBRARY_DIRS}\n )\n\n find_package_handle_standard_args(${comp}\n FOUND_VAR ${comp}_FOUND\n REQUIRED_VARS ${compname}_INCLUDE_DIR ${compname}_LIBRARY)\n mark_as_advanced(${compname}_INCLUDE_DIR ${compname}_LIBRARY)\n\n list(APPEND XCB_INCLUDE_DIRS ${${compname}_INCLUDE_DIR})\n list(APPEND XCB_LIBRARIES ${${compname}_LIBRARY})\n\n if(NOT ${comp}_FOUND)\n set(XCB_FOUND false)\n endif()\nendforeach()\n\nlist(REMOVE_DUPLICATES XCB_INCLUDE_DIRS)" }, { "path": "CMake-Utils/setup_cpp.cmake", "content": "function(add_cpp_executable binary)\n\tadd_executable(${binary} ${ARGN})\n\t\n\ttarget_compile_options(${binary} \n\t\tINTERFACE \"${CMAKE_CXX_FLAGS} -O3 -fPIE -fuse-ld=lld -fvisibility=hidden\"\n\t) # -flto=thin -fsanitize=cfi \n\t# -fsanitize=address memory thread\n\t\n\tset_target_properties(${binary}\n\t\tPROPERTIES CXX_STANDARD 20\n\t\t\t\t\tLINKER_LANGUAGE CXX\n\t\t\t\t\tRUNTIME_OUTPUT_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}\n\t)\n\t\n\ttarget_compile_features(${binary}\n\t\tINTERFACE cxx_std_20\n\t)\n\t\n\ttarget_link_libraries(${binary}\n\t\tPUBLIC #pthread\n\t\t\t\t\t#stdc++\n\t\t\t\t\tfmt\n\t)\n\t\n\tmessage(\"-- [${binary}]\\tcpp executable build config\")\nendfunction(add_cpp_executable)\n\nfunction(add_cpp_executable_debug binary)\n\tadd_executable(${binary} ${ARGN})\n\n\ttarget_compile_options(${binary} \n\t\tINTERFACE \"${CMAKE_CXX_FLAGS} -O2 -fPIE -fuse-ld=lld -fvisibility=hidden -fsanitize=address -fsanitize=memory -fsanitize=thread -fno-sanitize-trap=cfi\"\n\t) # -flto=thin -fsanitize=cfi\n\t# -fsanitize=address memory thread\n\t\n\tset_target_properties(${binary}\n\t\tPROPERTIES CXX_STANDARD 20\n\t\t\t\t\tLINKER_LANGUAGE CXX\n\t\t\t\t\tRUNTIME_OUTPUT_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}\n\t)\n\t\n\ttarget_compile_features(${binary}\n\t\tINTERFACE cxx_std_20\n\t)\n\t\n\ttarget_link_libraries(${binary}\n\t\tPUBLIC #pthread\n\t\t\t\t\t#stdc++\n\t\t\t\t\tfmt\n\t)\n\t\n\tmessage(\"-- [${binary}]\\tcpp debug executable build config\")\nendfunction(add_cpp_executable_debug)\n" }, { "path": "CMake-Utils/setup_cuda.cmake", "content": "message(\"## setup cuda\")\n\n#Find CUDA\ninclude(CheckLanguage)\ncheck_language(CUDA)\n\nif(CMAKE_CUDA_COMPILER)\n\tenable_language(CUDA)\n\tmessage(\"-- cuda-compiler \" ${CMAKE_CUDA_COMPILER})\nelse()\n\tmessage(STATUS \"No CUDA support\")\nendif()\nset(CUDA_FOUND ${CMAKE_CUDA_COMPILER})\n\n#Set Architecture\nset(CMAKE_CUDA_ARCHITECTURES native)\n\n# reference: https://cliutils.gitlab.io/modern-cmake/chapters/packages/CUDA.html\nfunction(CUDA_CONVERT_FLAGS EXISTING_TARGET)\n\tget_property(old_flags\n\t\tTARGET ${EXISTING_TARGET}\n\t\tPROPERTY INTERFACE_COMPILE_OPTIONS\n\t)\n\tif(NOT \"${old_flags}\" STREQUAL \"\")\n\t\tstring(REPLACE \";\" \",\" CUDA_flags \"${old_flags}\")\n\t\tset_property(\n\t\t\tTARGET ${EXISTING_TARGET}\n\t\t\tPROPERTY INTERFACE_COMPILE_OPTIONS\n\t\t\t\"$<$>:${old_flags}>$<$>:-Xcompiler=${CUDA_flags}>\"\n\t\t)\n\tendif()\nendfunction()\n\n#Cmake does not handle linking correctly for separable compilation: https://gitlab.kitware.com/cmake/cmake/-/issues/22788\nfunction(GET_DEVICE_LINK_PATH TARGET_NAME ret)\n\tcmake_path(SET DEVICE_LINK_PATH ${CMAKE_BINARY_DIR})\n\tcmake_path(APPEND DEVICE_LINK_PATH \"CMakeFiles\")\n\tcmake_path(APPEND DEVICE_LINK_PATH ${TARGET_NAME}.dir)\n\tcmake_path(APPEND DEVICE_LINK_PATH ${CMAKE_BUILD_TYPE})\n\tcmake_path(APPEND DEVICE_LINK_PATH \"cmake_device_link.obj\")\n\tset(${ret} ${DEVICE_LINK_PATH} PARENT_SCOPE)\nendfunction()\n\nfunction(add_cuda_executable binary)\n\tif(CUDA_FOUND)\n\t\tadd_executable(${binary} ${ARGN})\n\n\t\t# seems not working\n\t\ttarget_compile_options(${binary} \n\t\t\tPRIVATE $<$,$>:-g> --expt-extended-lambda --expt-relaxed-constexpr --default-stream=per-thread --use_fast_math -lineinfo --ptxas-options=-allow-expensive-optimizations=true>\n\t\t)\n\n\t\ttarget_compile_features(${binary}\n\t\t\tPRIVATE cuda_std_17\n\t\t)\n\n\t\tset_target_properties(${binary}\n\t\t\tPROPERTIES\tCUDA_EXTENSIONS ON\n\t\t\t\t\t\tCUDA_SEPARABLE_COMPILATION OFF\n\t\t\t\t\t\t#LINKER_LANGUAGE CUDA\n\t\t\t\t\t\tRUNTIME_OUTPUT_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}\n\t\t)\n\n\t\tGET_DEVICE_LINK_PATH(${binary} DEVICE_LINK_PATH)\n\n\t\ttarget_link_libraries(${binary}\n\t\t\tPRIVATE mncuda\n\t\t)\n\n\t\ttarget_link_options(${binary}\n\t\t\tPRIVATE /NODEFAULTLIB:libcmt.lib\n\t\t)\n\n\t\tinstall(TARGETS\n\t\t\t${binary}\n\t\t)\n\n\t\tmessage(\"-- [${binary}]\\tcuda executable build config\")\n\tendif()\nendfunction(add_cuda_executable)\n\nfunction(add_cuda_library library)\n\tif(CUDA_FOUND)\n\tadd_library(${library} ${ARGN})\n\n\t# seems not working\n\ttarget_compile_options(${library} \n\t\tPUBLIC $<$,$>:-g> --expt-extended-lambda --expt-relaxed-constexpr --default-stream=per-thread --use_fast_math -lineinfo --ptxas-options=-allow-expensive-optimizations=true>\n\t)\n\n\t#target_link_options(${library} \n\t# PRIVATE $<$:-arch=sm_75>\n\t#)\n\n\ttarget_compile_features(${library}\n\t\tPRIVATE cuda_std_17\n\t)\n\n\tset_target_properties(${library}\n\t\tPROPERTIES\tCUDA_EXTENSIONS ON\n\t\t\t\t\tCUDA_SEPARABLE_COMPILATION OFF\n\t\t\t\t\tCUDA_RESOLVE_DEVICE_SYMBOLS OFF\n\t\t\t\t\tPOSITION_INDEPENDENT_CODE ON\n\t\t\t\t\t#LINKER_LANGUAGE CUDA\n\t)\n\n\ttarget_compile_definitions(${library} \n\t\tPUBLIC\tCMAKE_GENERATOR_PLATFORM=x64\n\t)\n\n\tmessage(\"-- [${library}]\\tcuda executable build config\")\n\tendif()\nendfunction(add_cuda_library)" }, { "path": "CMake-Utils/setup_externallibs.cmake", "content": "#####\nset(CPM_DOWNLOAD_LOCATION \"${CMAKE_BINARY_DIR}/cmake/CPM.cmake\")\nset(CPM_DOWNLOAD_VERSION 0.38.1)\n\nif(NOT (EXISTS ${CPM_DOWNLOAD_LOCATION} AND CPM_VERSION STREQUAL CPM_DOWNLOAD_VERSION))\n\tmessage(STATUS \"Downloading CPM.cmake\")\n\tfile(DOWNLOAD https://github.com/TheLartians/CPM.cmake/releases/download/v${CPM_DOWNLOAD_VERSION}/CPM.cmake ${CPM_DOWNLOAD_LOCATION})\nendif()\n\ninclude(${CPM_DOWNLOAD_LOCATION})\n#####\n\n#Suppress warning\ncmake_policy(SET CMP0077 NEW)\n\n# rapidjson\nCPMAddPackage(\n\tNAME rapidjson\n\tGIT_TAG 949c771b03de448bdedea80c44a4a5f65284bfeb\n\tGITHUB_REPOSITORY Tencent/rapidjson\n\tOPTIONS\n\t\t\"RAPIDJSON_BUILD_CXX11 Off\"\n\t\t\"RAPIDJSON_BUILD_CXX17 On\"\n)\nif(rapidjson_ADDED)\n\tadd_library(rapidjson\n\t\tINTERFACE IMPORTED\n\t)\n\ttarget_include_directories(rapidjson\n\t\tSYSTEM INTERFACE ${rapidjson_SOURCE_DIR}/include\n\t)\nendif()\n\n# cxxopts\nCPMAddPackage(\n\tNAME cxxopts\n\tGITHUB_REPOSITORY jarro2783/cxxopts\n\tVERSION 2.2.0\n\tOPTIONS\n\t\t\"CXXOPTS_BUILD_EXAMPLES Off\"\n\t\t\"CXXOPTS_BUILD_TESTS Off\"\n)\n\n# spdlog\nCPMAddPackage(\n\tNAME spdlog\n\tVERSION 1.7.0\n\tGITHUB_REPOSITORY gabime/spdlog\n)\n\n#Set new timestamps\ncmake_policy(SET CMP0135 NEW)\nset(CMAKE_POLICY_DEFAULT_CMP0135 NEW)\n\n# ranges\nCPMAddPackage(\n\tNAME range-v3\n\tURL https://github.com/ericniebler/range-v3/archive/0.10.0.zip\n\tVERSION 0.10.0\n\t# the range-v3 CMakeLists screws with configuration options\n\tDOWNLOAD_ONLY True\n)\nif(range-v3_ADDED) \n\tadd_library(range-v3\n\t\tINTERFACE IMPORTED\n\t)\n\ttarget_include_directories(range-v3\n\t\tSYSTEM INTERFACE ${range-v3_SOURCE_DIR}/include\n\t)\nendif()\n\n# fmt\nCPMAddPackage(\n\tNAME fmt\n\tGIT_TAG 6.2.1\n\tGITHUB_REPOSITORY fmtlib/fmt\n)\nif(fmt_ADDED) \n\ttarget_include_directories(fmt\n\t\tSYSTEM INTERFACE ${fmt_SOURCE_DIR}/include\n\t)\nendif()\n\n# glm\nCPMAddPackage(\n\tNAME glm\n\tGIT_TAG 0.9.9.8\n\tGITHUB_REPOSITORY g-truc/glm\n)\n\n# filesystem\nCPMAddPackage(\n\tNAME filesystem \n\tGITHUB_REPOSITORY gulrak/filesystem\n\tVERSION 1.3.4\n)\nif(filesystem_ADDED) \n\tadd_library(filesystem\n\t\tINTERFACE IMPORTED\n\t)\n\ttarget_include_directories(filesystem\n\t\tSYSTEM INTERFACE ${filesystem_SOURCE_DIR}/include\n\t)\nendif()" }, { "path": "CMake-Utils/setup_python.cmake", "content": "function(add_python_library library)\n add_library(${library} MODULE ${ARGN})\n target_compile_options(${library} \n INTERFACE \"${CMAKE_CXX_FLAGS} -O3 -fuse-ld=lld \n -fvisibility=hidden -fsized-deallocation\") # -flto=thin -fsanitize=cfi\n set_target_properties(${library}\n PROPERTIES CPP_STANDARD 14\n PREFIX \"${PYTHON_MODULE_PREFIX}\"\n SUFFIX \"${PYTHON_MODULE_EXTENSION}\"\n LIBRARY_OUTPUT_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}\n )\n target_compile_definitions(${library} \n INTERFACE CMAKE_GENERATOR_PLATFORM=x64\n )\n target_compile_features(${library} INTERFACE cxx_std_14)\n target_link_libraries(${library}\n PRIVATE pybind11::module\n )\n message(\"-- [${library}]\\tpython library build config\")\nendfunction(add_python_library)\n" }, { "path": "CMakeLists.txt", "content": "cmake_minimum_required(VERSION 3.15) # support relative path\n\nmessage(\"===============================================================\")\n\ninclude(\"project_info.in\")\nproject(Mn \n VERSION ${project_version}\n DESCRIPTION ${project_description}\n LANGUAGES CXX CUDA\n)\n\noption(BUILD_SHARED_LIBS \"Enable compilation of shared libraries\" OFF)\n\n#Fixes https://gitlab.kitware.com/cmake/cmake/-/issues/24154 for older cmake versions\nset(CMAKE_INCLUDE_SYSTEM_FLAG_CUDA \"-isystem \")\n\nlist(APPEND CMAKE_MODULE_PATH ${CMAKE_CURRENT_SOURCE_DIR}/CMake)\ninclude(CMake-Utils/setup_cpp.cmake)\ninclude(CMake-Utils/setup_cuda.cmake)\ninclude(CMake-Utils/setup_externallibs.cmake)\n\n\nadd_subdirectory(Externals)\n\n# header only libraries\ninclude_directories(\n\tSYSTEM\n\tExternals/variant\n\tExternals/optional\n\tExternals/function_ref\n)\n\nmessage(\"===============================================================\")\n\ninclude_directories(Library)\nadd_subdirectory(Library)\nadd_subdirectory(Projects)\n" }, { "path": "Externals/CMakeLists.txt", "content": "find_package(Git)\ninclude(FetchContent)\ninclude(ExternalProject)\ninclude(DownloadProject)\n\n# partio\nmessage(\"## building partio\")\nadd_subdirectory(partio)\n\n# optional\n#FetchContent_Declare(\n# optional\n# GIT_REPOSITORY https://github.com/TartanLlama/optional.git\n# GIT_TAG 83a0b49e5e9571438c3ebae638e9a37502911b8c\n#)\n#FetchContent_MakeAvailable(optional)\n\n# function_ref\n#FetchContent_Declare(\n# function_ref\n# GIT_REPOSITORY https://github.com/TartanLlama/function_ref.git\n# GIT_TAG 556c2c3fbfc144971c01ba6d177aaab48cab6870\n#)\n##FetchContent_MakeAvailable(function_ref)\n#if (NOT function_ref_POPULATED)\n# FetchContent_Populate(function_ref)\n#endif()\n\n# variant\n#FetchContent_Declare(\n# variant\n# GIT_REPOSITORY https://github.com/mpark/variant.git\n# GIT_TAG 4988879a9f5a95d72308eca2b1779db6ed9b135d\n#)\n#FetchContent_MakeAvailable(variant)\n" }, { "path": "Externals/SDFGen/CMakeLists.txt", "content": "cmake_minimum_required(VERSION 2.6)\nProject(\"SDFGen\")\n\n# Set the build type. Options are:\n# Coverage : w/ debug symbols, w/o optimization, w/ code-coverage\n# Debug : w/ debug symbols, w/o optimization\n# Release : w/o debug symbols, w/ optimization\n# RelWithDebInfo : w/ debug symbols, w/ optimization\n# MinSizeRel : w/o debug symbols, w/ optimization, stripped binaries\n\n# SET(CMAKE_BUILD_TYPE Coverage)\nSET(CMAKE_BUILD_TYPE Release)\n\n#set the default path for built executables to the \"bin\" directory\nset(EXECUTABLE_OUTPUT_PATH ${CMAKE_CURRENT_BINARY_DIR}/bin)\n\n#These flags might not work on every system, especially the release flags, comment out as needed\nset(CMAKE_CXX_FLAGS \"-O3\")\nset(CMAKE_CXX_FLAGS_DEBUG \"-O0 -g\")\nset(CMAKE_CXX_FLAGS_RELEASE \"-O3 -march=native\")\n\n#checks if VTK is available\nfind_package(VTK QUIET)\nif(VTK_FOUND)\n\tset(HAVE_VTK 1)\nendif()\n\n#Generates config.h replacing expressions in config.h.in with actual values\nconfigure_file(\n \"${CMAKE_CURRENT_SOURCE_DIR}/config.h.in\"\n \"${CMAKE_CURRENT_SOURCE_DIR}/config.h\"\n)\n\nadd_executable(${PROJECT_NAME} main.cpp makelevelset3.cpp)\n\nif(VTK_FOUND)\n\tinclude_directories(${VTK_INCLUDE_DIRS})\n\ttarget_link_libraries(${PROJECT_NAME} ${VTK_LIBRARIES})\nendif()" }, { "path": "Externals/SDFGen/README.md", "content": "# SDFGen\nA simple commandline utility to generate grid-based signed distance field (level set) generator from triangle meshes, using code from Robert Bridson's website.\n\n\nThe MIT License (MIT)\n\nCopyright (c) 2015, Christopher Batty\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n" }, { "path": "Externals/SDFGen/array1.h", "content": "#ifndef ARRAY1_H\n#define ARRAY1_H\n\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n\n// In this file:\n// Array1: a dynamic 1D array for plain-old-data (not objects)\n// WrapArray1: a 1D array wrapper around an existing array (perhaps objects, perhaps data)\n// For the most part std::vector operations are supported, though for the Wrap version\n// note that memory is never allocated/deleted and constructor/destructors are never called\n// from within the class, thus only shallow copies can be made and some operations such as\n// resize() and push_back() are limited.\n// Note: for the most part assertions are done with assert(), not exceptions...\n\n// gross template hacking to determine if a type is integral or not\nstruct Array1True {};\nstruct Array1False {};\ntemplate struct Array1IsIntegral{ typedef Array1False type; }; // default: no (specializations to yes follow)\ntemplate<> struct Array1IsIntegral{ typedef Array1True type; };\ntemplate<> struct Array1IsIntegral{ typedef Array1True type; };\ntemplate<> struct Array1IsIntegral{ typedef Array1True type; };\ntemplate<> struct Array1IsIntegral{ typedef Array1True type; };\ntemplate<> struct Array1IsIntegral{ typedef Array1True type; };\ntemplate<> struct Array1IsIntegral{ typedef Array1True type; };\ntemplate<> struct Array1IsIntegral{ typedef Array1True type; };\ntemplate<> struct Array1IsIntegral{ typedef Array1True type; };\ntemplate<> struct Array1IsIntegral{ typedef Array1True type; };\ntemplate<> struct Array1IsIntegral{ typedef Array1True type; };\ntemplate<> struct Array1IsIntegral{ typedef Array1True type; };\ntemplate<> struct Array1IsIntegral{ typedef Array1True type; };\n\n//============================================================================\ntemplate\nstruct Array1\n{\n // STL-friendly typedefs\n\n typedef T* iterator;\n typedef const T* const_iterator;\n typedef unsigned long size_type;\n typedef long difference_type;\n typedef T& reference;\n typedef const T& const_reference;\n typedef T value_type;\n typedef T* pointer;\n typedef const T* const_pointer;\n typedef std::reverse_iterator reverse_iterator;\n typedef std::reverse_iterator const_reverse_iterator;\n\n // the actual representation\n\n unsigned long n;\n unsigned long max_n;\n T* data;\n\n // STL vector's interface, with additions, but only valid when used with plain-old-data\n\n Array1(void)\n : n(0), max_n(0), data(0)\n {}\n\n // note: default initial values are zero\n Array1(unsigned long n_)\n : n(0), max_n(0), data(0)\n {\n if(n_>ULONG_MAX/sizeof(T)) throw std::bad_alloc();\n data=(T*)std::calloc(n_, sizeof(T));\n if(!data) throw std::bad_alloc();\n n=n_;\n max_n=n_;\n }\n\n Array1(unsigned long n_, const T& value)\n : n(0), max_n(0), data(0)\n {\n if(n_>ULONG_MAX/sizeof(T)) throw std::bad_alloc();\n data=(T*)std::calloc(n_, sizeof(T));\n if(!data) throw std::bad_alloc();\n n=n_;\n max_n=n_;\n for(unsigned long i=0; iULONG_MAX/sizeof(T)) throw std::bad_alloc();\n data=(T*)std::calloc(max_n_, sizeof(T));\n if(!data) throw std::bad_alloc();\n n=n_;\n max_n=max_n_;\n for(unsigned long i=0; iULONG_MAX/sizeof(T)) throw std::bad_alloc();\n data=(T*)std::calloc(n_, sizeof(T));\n if(!data) throw std::bad_alloc();\n n=n_;\n max_n=n_;\n assert(data_);\n std::memcpy(data, data_, n*sizeof(T));\n }\n\n Array1(unsigned long n_, const T* data_, unsigned long max_n_)\n : n(0), max_n(0), data(0)\n {\n assert(n_<=max_n_);\n if(max_n_>ULONG_MAX/sizeof(T)) throw std::bad_alloc();\n data=(T*)std::calloc(max_n_, sizeof(T));\n if(!data) throw std::bad_alloc();\n max_n=max_n_;\n n=n_;\n assert(data_);\n std::memcpy(data, data_, n*sizeof(T));\n }\n\n Array1(const Array1 &x)\n : n(0), max_n(0), data(0)\n {\n data=(T*)std::malloc(x.n*sizeof(T));\n if(!data) throw std::bad_alloc();\n n=x.n;\n max_n=x.n;\n std::memcpy(data, x.data, n*sizeof(T));\n }\n\n ~Array1(void)\n {\n std::free(data);\n#ifndef NDEBUG\n data=0;\n n=max_n=0;\n#endif\n }\n\n const T& operator[](unsigned long i) const\n { return data[i]; }\n\n T& operator[](unsigned long i)\n { return data[i]; }\n\n // these are range-checked (in debug mode) versions of operator[], like at()\n const T& operator()(unsigned long i) const\n {\n assert(i& operator=(const Array1& x)\n {\n if(max_n& x) const\n {\n if(n!=x.n) return false;\n for(unsigned long i=0; i& x) const\n {\n if(n!=x.n) return true;\n for(unsigned long i=0; i& x) const\n {\n for(unsigned long i=0; i(const Array1& x) const\n {\n for(unsigned long i=0; ix[i]) return true;\n else if(x[i]>data[i]) return false;\n }\n return n>x.n;\n }\n\n bool operator<=(const Array1& x) const\n {\n for(unsigned long i=0; i=(const Array1& x) const\n {\n for(unsigned long i=0; ix[i]) return true;\n else if(x[i]>data[i]) return false;\n }\n return n>=x.n;\n }\n\n void add_unique(const T& value)\n {\n for(unsigned long i=0; imax_n){\n if(num>ULONG_MAX/sizeof(T)) throw std::bad_alloc();\n std::free(data);\n data=(T*)std::malloc(num*sizeof(T));\n if(!data) throw std::bad_alloc();\n max_n=num;\n }\n n=num;\n std::memcpy(data, copydata, n*sizeof(T));\n }\n\n template\n void assign(InputIterator first, InputIterator last)\n { assign_(first, last, typename Array1IsIntegral::type()); }\n\n template\n void assign_(InputIterator first, InputIterator last, Array1True check)\n { fill(first, last); }\n\n template\n void assign_(InputIterator first, InputIterator last, Array1False check)\n {\n unsigned long i=0;\n InputIterator p=first;\n for(; p!=last; ++p, ++i){\n if(i==max_n) grow();\n data[i]=*p;\n }\n n=i;\n }\n\n const T& at(unsigned long i) const\n {\n assert(i0);\n return data[n-1];\n }\n\n T& back(void)\n {\n assert(data && n>0);\n return data[n-1];\n }\n\n const T* begin(void) const\n { return data; }\n\n T* begin(void)\n { return data; }\n\n unsigned long capacity(void) const\n { return max_n; }\n\n void clear(void)\n {\n std::free(data);\n data=0;\n max_n=0;\n n=0;\n }\n\n bool empty(void) const\n { return n==0; }\n\n const T* end(void) const\n { return data+n; }\n\n T* end(void)\n { return data+n; }\n\n void erase(unsigned long index)\n {\n assert(indexmax_n){\n if(num>ULONG_MAX/sizeof(T)) throw std::bad_alloc();\n std::free(data);\n data=(T*)std::malloc(num*sizeof(T));\n if(!data) throw std::bad_alloc();\n max_n=num;\n }\n n=num;\n for(unsigned long i=0; i0);\n return *data;\n }\n\n T& front(void)\n {\n assert(n>0);\n return *data;\n }\n\n void grow(void)\n {\n unsigned long new_size=(max_n*sizeof(T)index; --i)\n data[i]=data[i-1];\n data[index]=entry;\n }\n\n unsigned long max_size(void) const\n { return ULONG_MAX/sizeof(T); }\n\n void pop_back(void)\n {\n assert(n>0);\n --n;\n }\n\n void push_back(const T& value)\n {\n if(n==max_n) grow();\n data[n++]=value;\n }\n\n reverse_iterator rbegin(void)\n { return reverse_iterator(end()); }\n\n const_reverse_iterator rbegin(void) const\n { return const_reverse_iterator(end()); }\n\n reverse_iterator rend(void)\n { return reverse_iterator(begin()); }\n\n const_reverse_iterator rend(void) const\n { return const_reverse_iterator(begin()); }\n\n void reserve(unsigned long r)\n {\n if(r>ULONG_MAX/sizeof(T)) throw std::bad_alloc();\n T *new_data=(T*)std::realloc(data, r*sizeof(T));\n if(!new_data) throw std::bad_alloc();\n data=new_data;\n max_n=r;\n }\n\n void resize(unsigned long n_)\n {\n if(n_>max_n) reserve(n_);\n n=n_;\n }\n\n void resize(unsigned long n_, const T& value)\n {\n if(n_>max_n) reserve(n_);\n if(n& x)\n {\n std::swap(n, x.n);\n std::swap(max_n, x.max_n);\n std::swap(data, x.data);\n }\n\n // resize the array to avoid wasted space, without changing contents\n // (Note: realloc, at least on some platforms, will not do the trick)\n void trim(void)\n {\n if(n==max_n) return;\n T *new_data=(T*)std::malloc(n*sizeof(T));\n if(!new_data) return;\n std::memcpy(new_data, data, n*sizeof(T));\n std::free(data);\n data=new_data;\n max_n=n;\n }\n};\n\n// some common arrays\n\ntypedef Array1 Array1d;\ntypedef Array1 Array1f;\ntypedef Array1 Array1ll;\ntypedef Array1 Array1ull;\ntypedef Array1 Array1i;\ntypedef Array1 Array1ui;\ntypedef Array1 Array1s;\ntypedef Array1 Array1us;\ntypedef Array1 Array1c;\ntypedef Array1 Array1uc;\n\n//============================================================================\ntemplate\nstruct WrapArray1\n{\n // STL-friendly typedefs\n\n typedef T* iterator;\n typedef const T* const_iterator;\n typedef unsigned long size_type;\n typedef long difference_type;\n typedef T& reference;\n typedef const T& const_reference;\n typedef T value_type;\n typedef T* pointer;\n typedef const T* const_pointer;\n typedef std::reverse_iterator reverse_iterator;\n typedef std::reverse_iterator const_reverse_iterator;\n\n // the actual representation\n\n unsigned long n;\n unsigned long max_n;\n T* data;\n\n // most of STL vector's interface, with a few changes\n\n WrapArray1(void)\n : n(0), max_n(0), data(0)\n {}\n\n WrapArray1(unsigned long n_, T* data_)\n : n(n_), max_n(n_), data(data_)\n { assert(data || max_n==0); }\n\n WrapArray1(unsigned long n_, T* data_, unsigned long max_n_)\n : n(n_), max_n(max_n_), data(data_)\n {\n assert(n<=max_n);\n assert(data || max_n==0);\n }\n\n // Allow for simple shallow copies of existing arrays\n // Note that if the underlying arrays change where their data is, the WrapArray may be screwed up\n\n WrapArray1(Array1& a)\n : n(a.n), max_n(a.max_n), data(a.data)\n {}\n\n WrapArray1(std::vector& a)\n : n(a.size()), max_n(a.capacity()), data(&a[0])\n {}\n\n void init(unsigned long n_, T* data_, unsigned long max_n_)\n {\n assert(n_<=max_n_);\n assert(data_ || max_n_==0);\n n=n_;\n max_n=max_n_;\n data=data_;\n }\n\n const T& operator[](unsigned long i) const\n { return data[i]; }\n\n T& operator[](unsigned long i)\n { return data[i]; }\n\n // these are range-checked (in debug mode) versions of operator[], like at()\n const T& operator()(unsigned long i) const\n {\n assert(i& x) const\n {\n if(n!=x.n) return false;\n for(unsigned long i=0; i& x) const\n {\n if(n!=x.n) return true;\n for(unsigned long i=0; i& x) const\n {\n for(unsigned long i=0; i(const WrapArray1& x) const\n {\n for(unsigned long i=0; ix[i]) return true;\n else if(x[i]>data[i]) return false;\n }\n return n>x.n;\n }\n\n bool operator<=(const WrapArray1& x) const\n {\n for(unsigned long i=0; i=(const WrapArray1& x) const\n {\n for(unsigned long i=0; ix[i]) return true;\n else if(x[i]>data[i]) return false;\n }\n return n>=x.n;\n }\n\n void add_unique(const T& value)\n {\n for(unsigned long i=0; i\n void assign(InputIterator first, InputIterator last)\n { assign_(first, last, typename Array1IsIntegral::type()); }\n\n template\n void assign_(InputIterator first, InputIterator last, Array1True check)\n { fill(first, last); }\n\n template\n void assign_(InputIterator first, InputIterator last, Array1False check)\n {\n unsigned long i=0;\n InputIterator p=first;\n for(; p!=last; ++p, ++i){\n assert(i0);\n return data[n-1];\n }\n\n T& back(void)\n {\n assert(data && n>0);\n return data[n-1];\n }\n\n const T* begin(void) const\n { return data; }\n\n T* begin(void)\n { return data; }\n\n unsigned long capacity(void) const\n { return max_n; }\n\n void clear(void)\n { n=0; }\n\n bool empty(void) const\n { return n==0; }\n\n const T* end(void) const\n { return data+n; }\n\n T* end(void)\n { return data+n; }\n\n void erase(unsigned long index)\n {\n assert(index0);\n return *data;\n }\n\n T& front(void)\n {\n assert(n>0);\n return *data;\n }\n\n void insert(unsigned long index, const T& entry)\n {\n assert(index<=n);\n push_back(back());\n for(unsigned long i=n-1; i>index; --i)\n data[i]=data[i-1];\n data[index]=entry;\n }\n\n unsigned long max_size(void) const\n { return max_n; }\n\n void pop_back(void)\n {\n assert(n>0);\n --n;\n }\n\n void push_back(const T& value)\n {\n assert(n& x)\n {\n std::swap(n, x.n);\n std::swap(max_n, x.max_n);\n std::swap(data, x.data);\n }\n};\n\n// some common arrays\n\ntypedef WrapArray1 WrapArray1d;\ntypedef WrapArray1 WrapArray1f;\ntypedef WrapArray1 WrapArray1ll;\ntypedef WrapArray1 WrapArray1ull;\ntypedef WrapArray1 WrapArray1i;\ntypedef WrapArray1 WrapArray1ui;\ntypedef WrapArray1 WrapArray1s;\ntypedef WrapArray1 WrapArray1us;\ntypedef WrapArray1 WrapArray1c;\ntypedef WrapArray1 WrapArray1uc;\n\n#endif\n" }, { "path": "Externals/SDFGen/array2.h", "content": "#ifndef ARRAY2_H\n#define ARRAY2_H\n\n#include \"array1.h\"\n#include \n#include \n#include \n\ntemplate >\nstruct Array2\n{\n // STL-friendly typedefs\n\n typedef typename ArrayT::iterator iterator;\n typedef typename ArrayT::const_iterator const_iterator;\n typedef typename ArrayT::size_type size_type;\n typedef long difference_type;\n typedef T& reference;\n typedef const T& const_reference;\n typedef T value_type;\n typedef T* pointer;\n typedef const T* const_pointer;\n typedef typename ArrayT::reverse_iterator reverse_iterator;\n typedef typename ArrayT::const_reverse_iterator const_reverse_iterator;\n\n // the actual representation\n\n int ni, nj;\n ArrayT a;\n\n // the interface\n\n Array2(void)\n : ni(0), nj(0)\n {}\n\n Array2(int ni_, int nj_)\n : ni(ni_), nj(nj_), a(ni_*nj_)\n { assert(ni_>=0 && nj>=0); }\n\n Array2(int ni_, int nj_, ArrayT& a_)\n : ni(ni_), nj(nj_), a(a_)\n { assert(ni_>=0 && nj>=0); }\n\n Array2(int ni_, int nj_, const T& value)\n : ni(ni_), nj(nj_), a(ni_*nj_, value)\n { assert(ni_>=0 && nj>=0); }\n\n Array2(int ni_, int nj_, const T& value, size_type max_n_)\n : ni(ni_), nj(nj_), a(ni_*nj_, value, max_n_)\n { assert(ni_>=0 && nj>=0); }\n\n Array2(int ni_, int nj_, T* data_)\n : ni(ni_), nj(nj_), a(ni_*nj_, data_)\n { assert(ni_>=0 && nj>=0); }\n\n Array2(int ni_, int nj_, T* data_, size_type max_n_)\n : ni(ni_), nj(nj_), a(ni_*nj_, data_, max_n_)\n { assert(ni_>=0 && nj>=0); }\n\n template\n Array2(Array2& other)\n : ni(other.ni), nj(other.nj), a(other.a)\n {}\n\n ~Array2(void)\n {\n#ifndef NDEBUG\n ni=nj=0;\n#endif\n }\n\n const T& operator()(int i, int j) const\n {\n assert(i>=0 && i=0 && j=0 && i=0 && j& x) const\n { return ni==x.ni && nj==x.nj && a==x.a; }\n\n bool operator!=(const Array2& x) const\n { return ni!=x.ni || nj!=x.nj || a!=x.a; }\n\n bool operator<(const Array2& x) const\n {\n if(nix.ni) return false;\n if(njx.nj) return false;\n return a(const Array2& x) const\n {\n if(ni>x.ni) return true; else if(nix.nj) return true; else if(njx.a;\n }\n\n bool operator<=(const Array2& x) const\n {\n if(nix.ni) return false;\n if(njx.nj) return false;\n return a<=x.a;\n }\n\n bool operator>=(const Array2& x) const\n {\n if(ni>x.ni) return true; else if(nix.nj) return true; else if(nj=x.a;\n }\n\n void assign(const T& value)\n { a.assign(value); }\n\n void assign(int ni_, int nj_, const T& value)\n {\n a.assign(ni_*nj_, value);\n ni=ni_;\n nj=nj_;\n }\n \n void assign(int ni_, int nj_, const T* copydata)\n {\n a.assign(ni_*nj_, copydata);\n ni=ni_;\n nj=nj_;\n }\n \n const T& at(int i, int j) const\n {\n assert(i>=0 && i=0 && j=0 && i=0 && j=0 && nj_>=0);\n a.resize(ni_*nj_);\n ni=ni_;\n nj=nj_;\n }\n\n void resize(int ni_, int nj_, const T& value)\n {\n assert(ni_>=0 && nj_>=0);\n a.resize(ni_*nj_, value);\n ni=ni_;\n nj=nj_;\n }\n\n void set_zero(void)\n { a.set_zero(); }\n\n size_type size(void) const\n { return a.size(); }\n\n void swap(Array2& x)\n {\n std::swap(ni, x.ni);\n std::swap(nj, x.nj);\n a.swap(x.a);\n }\n\n void trim(void)\n { a.trim(); }\n};\n\n// some common arrays\n\ntypedef Array2 > Array2d;\ntypedef Array2 > Array2f;\ntypedef Array2 > Array2ll;\ntypedef Array2 > Array2ull;\ntypedef Array2 > Array2i;\ntypedef Array2 > Array2ui;\ntypedef Array2 > Array2s;\ntypedef Array2 > Array2us;\ntypedef Array2 > Array2c;\ntypedef Array2 > Array2uc;\n\n// and wrapped versions\n\ntypedef Array2 > WrapArray2d;\ntypedef Array2 > WrapArray2f;\ntypedef Array2 > WrapArray2ll;\ntypedef Array2 > WrapArray2ull;\ntypedef Array2 > WrapArray2i;\ntypedef Array2 > WrapArray2ui;\ntypedef Array2 > WrapArray2s;\ntypedef Array2 > WrapArray2us;\ntypedef Array2 > WrapArray2c;\ntypedef Array2 > WrapArray2uc;\n\n#endif\n" }, { "path": "Externals/SDFGen/array3.h", "content": "#ifndef ARRAY3_H\n#define ARRAY3_H\n\n#include \"array1.h\"\n#include \n#include \n#include \n\ntemplate >\nstruct Array3\n{\n // STL-friendly typedefs\n\n typedef typename ArrayT::iterator iterator;\n typedef typename ArrayT::const_iterator const_iterator;\n typedef typename ArrayT::size_type size_type;\n typedef long difference_type;\n typedef T& reference;\n typedef const T& const_reference;\n typedef T value_type;\n typedef T* pointer;\n typedef const T* const_pointer;\n typedef typename ArrayT::reverse_iterator reverse_iterator;\n typedef typename ArrayT::const_reverse_iterator const_reverse_iterator;\n\n // the actual representation\n\n int ni, nj, nk;\n ArrayT a;\n\n // the interface\n\n Array3(void)\n : ni(0), nj(0), nk(0)\n {}\n\n Array3(int ni_, int nj_, int nk_)\n : ni(ni_), nj(nj_), nk(nk_), a(ni_*nj_*nk_)\n { assert(ni_>=0 && nj_>=0 && nk_>=0); }\n\n Array3(int ni_, int nj_, int nk_, ArrayT& a_)\n : ni(ni_), nj(nj_), nk(nk_), a(a_)\n { assert(ni_>=0 && nj_>=0 && nk_>=0); }\n\n Array3(int ni_, int nj_, int nk_, const T& value)\n : ni(ni_), nj(nj_), nk(nk_), a(ni_*nj_*nk_, value)\n { assert(ni_>=0 && nj_>=0 && nk_>=0); }\n\n Array3(int ni_, int nj_, int nk_, const T& value, size_type max_n_)\n : ni(ni_), nj(nj_), nk(nk_), a(ni_*nj_*nk_, value, max_n_)\n { assert(ni_>=0 && nj_>=0 && nk_>=0); }\n\n Array3(int ni_, int nj_, int nk_, T* data_)\n : ni(ni_), nj(nj_), nk(nk_), a(ni_*nj_*nk_, data_)\n { assert(ni_>=0 && nj_>=0 && nk_>=0); }\n\n Array3(int ni_, int nj_, int nk_, T* data_, size_type max_n_)\n : ni(ni_), nj(nj_), nk(nk_), a(ni_*nj_*nk_, data_, max_n_)\n { assert(ni_>=0 && nj_>=0 && nk_>=0); }\n\n ~Array3(void)\n {\n#ifndef NDEBUG\n ni=nj=0;\n#endif\n }\n\n const T& operator()(int i, int j, int k) const\n {\n assert(i>=0 && i=0 && j=0 && k=0 && i=0 && j=0 && k& x) const\n { return ni==x.ni && nj==x.nj && nk==x.nk && a==x.a; }\n\n bool operator!=(const Array3& x) const\n { return ni!=x.ni || nj!=x.nj || nk!=x.nk || a!=x.a; }\n\n bool operator<(const Array3& x) const\n {\n if(nix.ni) return false;\n if(njx.nj) return false;\n if(nkx.nk) return false;\n return a(const Array3& x) const\n {\n if(ni>x.ni) return true; else if(nix.nj) return true; else if(njx.nk) return true; else if(nkx.a;\n }\n\n bool operator<=(const Array3& x) const\n {\n if(nix.ni) return false;\n if(njx.nj) return false;\n if(nkx.nk) return false;\n return a<=x.a;\n }\n\n bool operator>=(const Array3& x) const\n {\n if(ni>x.ni) return true; else if(nix.nj) return true; else if(njx.nk) return true; else if(nk=x.a;\n }\n\n void assign(const T& value)\n { a.assign(value); }\n\n void assign(int ni_, int nj_, int nk_, const T& value)\n {\n a.assign(ni_*nj_*nk_, value);\n ni=ni_;\n nj=nj_;\n nk=nk_;\n }\n \n void assign(int ni_, int nj_, int nk_, const T* copydata)\n {\n a.assign(ni_*nj_*nk_, copydata);\n ni=ni_;\n nj=nj_;\n nk=nk_;\n }\n \n const T& at(int i, int j, int k) const\n {\n assert(i>=0 && i=0 && j=0 && k=0 && i=0 && j=0 && k=0 && nj_>=0 && nk_>=0);\n a.resize(ni_*nj_*nk_);\n ni=ni_;\n nj=nj_;\n nk=nk_;\n }\n\n void resize(int ni_, int nj_, int nk_, const T& value)\n {\n assert(ni_>=0 && nj_>=0 && nk_>=0);\n a.resize(ni_*nj_*nk_, value);\n ni=ni_;\n nj=nj_;\n nk=nk_;\n }\n\n void set_zero(void)\n { a.set_zero(); }\n\n size_type size(void) const\n { return a.size(); }\n\n void swap(Array3& x)\n {\n std::swap(ni, x.ni);\n std::swap(nj, x.nj);\n std::swap(nk, x.nk);\n a.swap(x.a);\n }\n\n void trim(void)\n { a.trim(); }\n};\n\n// some common arrays\n\ntypedef Array3 > Array3d;\ntypedef Array3 > Array3f;\ntypedef Array3 > Array3ll;\ntypedef Array3 > Array3ull;\ntypedef Array3 > Array3i;\ntypedef Array3 > Array3ui;\ntypedef Array3 > Array3s;\ntypedef Array3 > Array3us;\ntypedef Array3 > Array3c;\ntypedef Array3 > Array3uc;\n\n#endif\n" }, { "path": "Externals/SDFGen/config.h.in", "content": "#ifndef SDFGEN_CONFIG_H\n#define SDFGEN_CONFIG_H\n\n/*\n * Configuration Header for SDFGEN\n */\n \n/// Configured libraries\n#cmakedefine HAVE_VTK\n\n#endif //SDFGEN_CONFIG_H\n" }, { "path": "Externals/SDFGen/hashgrid.h", "content": "#ifndef HASHGRID_H\n#define HASHGRID_H\n\n#include \"hashtable.h\"\n#include \"vec.h\"\n\n//========================================================= first do 2D ============================\n\ntemplate\nstruct HashGrid2\n{\n double dx, overdx; // side-length of a grid cell and its reciprocal\n HashTable grid;\n\n explicit HashGrid2(double dx_=1, int expected_size=512)\n : dx(dx_), overdx(1/dx_), grid(expected_size)\n {}\n\n // only do this with an empty grid\n void set_grid_size(double dx_)\n { assert(size()==0); dx=dx_; overdx=1/dx; }\n\n void add_point(const Vec2d &x, const DataType &datum)\n { grid.add(round(x*overdx), datum); }\n\n void delete_point(const Vec2d &x, const DataType &datum)\n { grid.delete_entry(round(x*overdx), datum); }\n\n void add_box(const Vec2d &xmin, const Vec2d &xmax, const DataType &datum)\n {\n Vec2i imin=round(xmin*overdx), imax=round(xmax*overdx);\n for(int j=imin[1]; j<=imax[1]; ++j) for(int i=imin[0]; i<=imax[0]; ++i)\n grid.add(Vec2i(i,j), datum);\n }\n\n void delete_box(const Vec2d &xmin, const Vec2d &xmax, const DataType &datum)\n {\n Vec2i imin=round(xmin*overdx), imax=round(xmax*overdx);\n for(int j=imin[1]; j<=imax[1]; ++j) for(int i=imin[0]; i<=imax[0]; ++i)\n grid.delete_entry(Vec2i(i,j), datum);\n }\n\n unsigned int size(void) const\n { return grid.size(); }\n\n void clear(void)\n { grid.clear(); }\n\n void reserve(unsigned int expected_size)\n { grid.reserve(expected_size); }\n\n bool find_first_point(const Vec2d &x, DataType &datum) const\n { return grid.get_entry(round(x*overdx), datum); }\n\n bool find_point(const Vec2d &x, std::vector &data_list) const\n {\n data_list.resize(0);\n grid.append_all_entries(round(x*overdx), data_list);\n return data_list.size()>0;\n }\n\n bool find_box(const Vec2d &xmin, const Vec2d &xmax, std::vector &data_list) const\n {\n data_list.resize(0);\n Vec2i imin=round(xmin*overdx), imax=round(xmax*overdx);\n for(int j=imin[1]; j<=imax[1]; ++j) for(int i=imin[0]; i<=imax[0]; ++i)\n grid.append_all_entries(Vec2i(i,j), data_list);\n return data_list.size()>0;\n }\n};\n\n//==================================== and now in 3D =================================================\n\ntemplate\nstruct HashGrid3\n{\n double dx, overdx; // side-length of a grid cell and its reciprocal\n HashTable grid;\n\n explicit HashGrid3(double dx_=1, int expected_size=512)\n : dx(dx_), overdx(1/dx_), grid(expected_size)\n {}\n\n // only do this with an empty grid\n void set_grid_size(double dx_)\n { assert(size()==0); dx=dx_; overdx=1/dx; }\n\n void add_point(const Vec3d &x, const DataType &datum)\n { grid.add(round(x*overdx), datum); }\n\n void delete_point(const Vec3d &x, const DataType &datum)\n { grid.delete_entry(round(x*overdx), datum); }\n\n void add_box(const Vec3d &xmin, const Vec3d &xmax, const DataType &datum)\n {\n Vec3i imin=round(xmin*overdx), imax=round(xmax*overdx);\n for(int k=imin[2]; k<=imax[2]; ++k) for(int j=imin[1]; j<=imax[1]; ++j) for(int i=imin[0]; i<=imax[0]; ++i)\n grid.add(Vec3i(i,j,k), datum);\n }\n\n void delete_box(const Vec3d &xmin, const Vec3d &xmax, const DataType &datum)\n {\n Vec3i imin=round(xmin*overdx), imax=round(xmax*overdx);\n for(int k=imin[2]; k<=imax[2]; ++k) for(int j=imin[1]; j<=imax[1]; ++j) for(int i=imin[0]; i<=imax[0]; ++i)\n grid.delete_entry(Vec3i(i,j,k), datum);\n }\n \n unsigned int size(void) const\n { return grid.size(); }\n\n void clear(void)\n { grid.clear(); }\n\n void reserve(unsigned int expected_size)\n { grid.reserve(expected_size); }\n\n bool find_first_point(const Vec3d &x, DataType &index) const\n { return grid.get_entry(round(x*overdx), index); }\n\n bool find_point(const Vec3d &x, std::vector &data_list) const\n {\n data_list.resize(0);\n grid.append_all_entries(round(x*overdx), data_list);\n return data_list.size()>0;\n }\n\n bool find_box(const Vec3d &xmin, const Vec3d &xmax, std::vector &data_list) const\n {\n data_list.resize(0);\n Vec3i imin=round(xmin*overdx), imax=round(xmax*overdx);\n for(int k=imin[2]; k<=imax[2]; ++k) for(int j=imin[1]; j<=imax[1]; ++j) for(int i=imin[0]; i<=imax[0]; ++i)\n grid.append_all_entries(Vec3i(i, j, k), data_list);\n return data_list.size()>0;\n }\n};\n\n#endif\n" }, { "path": "Externals/SDFGen/hashtable.h", "content": "#ifndef HASHTABLE_H\n#define HASHTABLE_H\n\n#include \n#include \n#include \n\ntemplate\nstruct HashEntry\n{\n Key key;\n Data data;\n int next;\n};\n\n// a useful core hash function\ninline unsigned int hash(unsigned int k)\n{ return k*2654435769u; }\n\n// default hash function object\nstruct DefaultHashFunction\n{\n template\n unsigned int operator() (const Key &k) const { return hash(k); }\n};\n\nstruct equal\n{\n template\n bool operator() (const T &a, const T &b) const { return a==b; }\n};\n\ntemplate\nstruct HashTable\n{\n unsigned int table_rank;\n unsigned int table_bits;\n std::vector table;\n unsigned int num_entries;\n std::vector > pool;\n int free_list;\n const HashFunction hash_function;\n const KeyEqual key_equal;\n\n explicit HashTable(unsigned int expected_size=64)\n : hash_function(HashFunction()), key_equal(KeyEqual())\n { init(expected_size); }\n\n explicit HashTable(const HashFunction &hf, unsigned int expected_size=64)\n : hash_function(hf), key_equal(KeyEqual())\n { init(expected_size); }\n\n void init(unsigned int expected_size)\n {\n unsigned int i;\n num_entries=0;\n table_rank=4;\n while(1u<& data_return) const\n {\n unsigned int t=hash_function(k)&table_bits;\n int i=table[t];\n while(i!=-1){\n if(key_equal(k, pool[i].key)) data_return.push_back(pool[i].data);\n i=pool[i].next;\n }\n }\n\n Data &operator() (const Key &k, const Data &missing_data)\n {\n unsigned int t=hash_function(k)&table_bits;\n int i=table[t];\n while(i!=-1){\n if(key_equal(k, pool[i].key))\n return pool[i].data;\n i=pool[i].next;\n }\n add(k, missing_data); // note - this could cause the table to be resized, and t made out-of-date\n return pool[table[hash_function(k)&table_bits]].data; // we know that add() puts it here!\n }\n\n const Data &operator() (const Key &k, const Data &missing_data) const\n {\n unsigned int t=hash_function(k)&table_bits;\n int i=table[t];\n while(i!=-1){\n if(key_equal(k, pool[i].key))\n return pool[i].data;\n i=pool[i].next;\n }\n return missing_data;\n }\n\n void output_statistics() const\n {\n std::vector lengthcount(table.size());\n unsigned int t;\n int total=0;\n for(t=0; t0){\n std::cout<<\"length \"<0)\n maxlength=t;\n std::cout<<\"longest list: \"<\n #include \n #include \n #include \n #include \n#endif\n\n\n#include \n#include \n#include \n#include \n\nint main(int argc, char* argv[]) {\n \n if(argc != 4) {\n std::cout << \"SDFGen - A utility for converting closed oriented triangle meshes into grid-based signed distance fields.\\n\";\n std::cout << \"\\nThe output file format is:\";\n std::cout << \" \\n\";\n std::cout << \" \\n\";\n std::cout << \"\\n\";\n std::cout << \" [...]\\n\\n\";\n \n std::cout << \"(ni,nj,nk) are the integer dimensions of the resulting distance field.\\n\";\n std::cout << \"(origin_x,origin_y,origin_z) is the 3D position of the grid origin.\\n\";\n std::cout << \" is the grid spacing.\\n\\n\";\n std::cout << \" are the signed distance data values, in ascending order of i, then j, then k.\\n\";\n\n std::cout << \"The output filename will match that of the input, with the OBJ suffix replaced with SDF.\\n\\n\";\n\n std::cout << \"Usage: SDFGen \\n\\n\";\n std::cout << \"Where:\\n\";\n std::cout << \"\\t specifies a Wavefront OBJ (text) file representing a *triangle* mesh (no quad or poly meshes allowed). File must use the suffix \\\".obj\\\".\\n\";\n std::cout << \"\\t specifies the length of grid cell in the resulting distance field.\\n\";\n std::cout << \"\\t specifies the number of cells worth of padding between the object bound box and the boundary of the distance field grid. Minimum is 1.\\n\\n\";\n \n exit(-1);\n }\n\n std::string filename(argv[1]);\n if(filename.size() < 5 || filename.substr(filename.size()-4) != std::string(\".obj\")) {\n std::cerr << \"Error: Expected OBJ file with filename of the form .obj.\\n\";\n exit(-1);\n }\n\n std::stringstream arg2(argv[2]);\n float dx;\n arg2 >> dx;\n \n std::stringstream arg3(argv[3]);\n int padding;\n arg3 >> padding;\n\n if(padding < 1) padding = 1;\n //start with a massive inside out bound box.\n Vec3f min_box(std::numeric_limits::max(),std::numeric_limits::max(),std::numeric_limits::max()), \n max_box(-std::numeric_limits::max(),-std::numeric_limits::max(),-std::numeric_limits::max());\n \n std::cout << \"Reading data.\\n\";\n\n std::ifstream infile(argv[1]);\n if(!infile) {\n std::cerr << \"Failed to open. Terminating.\\n\";\n exit(-1);\n }\n\n int ignored_lines = 0;\n std::string line;\n std::vector vertList;\n std::vector faceList;\n while(!infile.eof()) {\n std::getline(infile, line);\n\n //.obj files sometimes contain vertex normals indicated by \"vn\"\n if(line.substr(0,1) == std::string(\"v\") && line.substr(0,2) != std::string(\"vn\")){\n std::stringstream data(line);\n char c;\n Vec3f point;\n data >> c >> point[0] >> point[1] >> point[2];\n vertList.push_back(point);\n update_minmax(point, min_box, max_box);\n }\n else if(line.substr(0,1) == std::string(\"f\")) {\n std::stringstream data(line);\n char c;\n int v0,v1,v2;\n data >> c >> v0 >> v1 >> v2;\n faceList.push_back(Vec3ui(v0-1,v1-1,v2-1));\n }\n else if( line.substr(0,2) == std::string(\"vn\") ){\n std::cerr << \"Obj-loader is not able to parse vertex normals, please strip them from the input file. \\n\";\n exit(-2); \n }\n else {\n ++ignored_lines; \n }\n }\n infile.close();\n \n if(ignored_lines > 0)\n std::cout << \"Warning: \" << ignored_lines << \" lines were ignored since they did not contain faces or vertices.\\n\";\n\n std::cout << \"Read in \" << vertList.size() << \" vertices and \" << faceList.size() << \" faces.\" << std::endl;\n\n //Add padding around the box.\n Vec3f unit(1,1,1);\n min_box -= padding*dx*unit;\n max_box += padding*dx*unit;\n Vec3ui sizes = Vec3ui((max_box - min_box)/dx);\n \n std::cout << \"Bound box size: (\" << min_box << \") to (\" << max_box << \") with dimensions \" << sizes << \".\" << std::endl;\n\n std::cout << \"Computing signed distance field.\\n\";\n Array3f phi_grid;\n make_level_set3(faceList, vertList, min_box, dx, sizes[0], sizes[1], sizes[2], phi_grid);\n\n std::string outname;\n\n #ifdef HAVE_VTK\n // If compiled with VTK, we can directly output a volumetric image format instead\n //Very hackily strip off file suffix.\n outname = filename.substr(0, filename.size()-4) + std::string(\".vti\");\n std::cout << \"Writing results to: \" << outname << \"\\n\";\n vtkSmartPointer output_volume = vtkSmartPointer::New();\n\n output_volume->SetDimensions(phi_grid.ni ,phi_grid.nj ,phi_grid.nk);\n output_volume->SetOrigin( phi_grid.ni*dx/2, phi_grid.nj*dx/2,phi_grid.nk*dx/2);\n output_volume->SetSpacing(dx,dx,dx);\n\n vtkSmartPointer distance = vtkSmartPointer::New();\n \n distance->SetNumberOfTuples(phi_grid.a.size());\n \n output_volume->GetPointData()->AddArray(distance);\n distance->SetName(\"Distance\");\n\n for(unsigned int i = 0; i < phi_grid.a.size(); ++i) {\n distance->SetValue(i, phi_grid.a[i]);\n }\n\n vtkSmartPointer writer =\n vtkSmartPointer::New();\n writer->SetFileName(outname.c_str());\n\n #if VTK_MAJOR_VERSION <= 5\n writer->SetInput(output_volume);\n #else\n writer->SetInputData(output_volume);\n #endif\n writer->Write();\n\n #else\n // if VTK support is missing, default back to the original ascii file-dump.\n //Very hackily strip off file suffix.\n outname = filename.substr(0, filename.size()-4) + std::string(\".sdf\");\n std::cout << \"Writing results to: \" << outname << \"\\n\";\n \n std::ofstream outfile( outname.c_str());\n outfile << phi_grid.ni << \" \" << phi_grid.nj << \" \" << phi_grid.nk << std::endl;\n outfile << min_box[0] << \" \" << min_box[1] << \" \" << min_box[2] << std::endl;\n outfile << dx << std::endl;\n for(unsigned int i = 0; i < phi_grid.a.size(); ++i) {\n outfile << phi_grid.a[i] << std::endl;\n }\n outfile.close();\n #endif\n\n std::cout << \"Processing complete.\\n\";\n\nreturn 0;\n}\n" }, { "path": "Externals/SDFGen/makelevelset3.cpp", "content": "#include \"makelevelset3.h\"\n\n// find distance x0 is from segment x1-x2\nstatic float point_segment_distance(const Vec3f &x0, const Vec3f &x1, const Vec3f &x2)\n{\n Vec3f dx(x2-x1);\n double m2=mag2(dx);\n // find parameter value of closest point on segment\n float s12=(float)(dot(x2-x0, dx)/m2);\n if(s12<0){\n s12=0;\n }else if(s12>1){\n s12=1;\n }\n // and find the distance\n return dist(x0, s12*x1+(1-s12)*x2);\n}\n\n// find distance x0 is from triangle x1-x2-x3\nstatic float point_triangle_distance(const Vec3f &x0, const Vec3f &x1, const Vec3f &x2, const Vec3f &x3)\n{\n // first find barycentric coordinates of closest point on infinite plane\n Vec3f x13(x1-x3), x23(x2-x3), x03(x0-x3);\n float m13=mag2(x13), m23=mag2(x23), d=dot(x13,x23);\n float invdet=1.f/max(m13*m23-d*d,1e-30f);\n float a=dot(x13,x03), b=dot(x23,x03);\n // the barycentric coordinates themselves\n float w23=invdet*(m23*a-d*b);\n float w31=invdet*(m13*b-d*a);\n float w12=1-w23-w31;\n if(w23>=0 && w31>=0 && w12>=0){ // if we're inside the triangle\n return dist(x0, w23*x1+w31*x2+w12*x3); \n }else{ // we have to clamp to one of the edges\n if(w23>0) // this rules out edge 2-3 for us\n return min(point_segment_distance(x0,x1,x2), point_segment_distance(x0,x1,x3));\n else if(w31>0) // this rules out edge 1-3\n return min(point_segment_distance(x0,x1,x2), point_segment_distance(x0,x2,x3));\n else // w12 must be >0, ruling out edge 1-2\n return min(point_segment_distance(x0,x1,x3), point_segment_distance(x0,x2,x3));\n }\n}\n\nstatic void check_neighbour(const std::vector &tri, const std::vector &x,\n Array3f &phi, Array3i &closest_tri,\n const Vec3f &gx, int i0, int j0, int k0, int i1, int j1, int k1)\n{\n if(closest_tri(i1,j1,k1)>=0){\n unsigned int p, q, r; assign(tri[closest_tri(i1,j1,k1)], p, q, r);\n float d=point_triangle_distance(gx, x[p], x[q], x[r]);\n if(d &tri, const std::vector &x,\n Array3f &phi, Array3i &closest_tri, const Vec3f &origin, float dx,\n int di, int dj, int dk)\n{\n int i0, i1;\n if(di>0){ i0=1; i1=phi.ni; }\n else{ i0=phi.ni-2; i1=-1; }\n int j0, j1;\n if(dj>0){ j0=1; j1=phi.nj; }\n else{ j0=phi.nj-2; j1=-1; }\n int k0, k1;\n if(dk>0){ k0=1; k1=phi.nk; }\n else{ k0=phi.nk-2; k1=-1; }\n for(int k=k0; k!=k1; k+=dk) for(int j=j0; j!=j1; j+=dj) for(int i=i0; i!=i1; i+=di){\n Vec3f gx(i*dx+origin[0], j*dx+origin[1], k*dx+origin[2]);\n check_neighbour(tri, x, phi, closest_tri, gx, i, j, k, i-di, j, k);\n check_neighbour(tri, x, phi, closest_tri, gx, i, j, k, i, j-dj, k);\n check_neighbour(tri, x, phi, closest_tri, gx, i, j, k, i-di, j-dj, k);\n check_neighbour(tri, x, phi, closest_tri, gx, i, j, k, i, j, k-dk);\n check_neighbour(tri, x, phi, closest_tri, gx, i, j, k, i-di, j, k-dk);\n check_neighbour(tri, x, phi, closest_tri, gx, i, j, k, i, j-dj, k-dk);\n check_neighbour(tri, x, phi, closest_tri, gx, i, j, k, i-di, j-dj, k-dk);\n }\n}\n\n// calculate twice signed area of triangle (0,0)-(x1,y1)-(x2,y2)\n// return an SOS-determined sign (-1, +1, or 0 only if it's a truly degenerate triangle)\nstatic int orientation(double x1, double y1, double x2, double y2, double &twice_signed_area)\n{\n twice_signed_area=y1*x2-x1*y2;\n if(twice_signed_area>0) return 1;\n else if(twice_signed_area<0) return -1;\n else if(y2>y1) return 1;\n else if(y2x2) return 1;\n else if(x1 &tri, const std::vector &x,\n const Vec3f &origin, float dx, int ni, int nj, int nk,\n Array3f &phi, const int exact_band)\n{\n phi.resize(ni, nj, nk);\n phi.assign((ni+nj+nk)*dx); // upper bound on distance\n Array3i closest_tri(ni, nj, nk, -1);\n Array3i intersection_count(ni, nj, nk, 0); // intersection_count(i,j,k) is # of tri intersections in (i-1,i]x{j}x{k}\n // we begin by initializing distances near the mesh, and figuring out intersection counts\n Vec3f ijkmin, ijkmax;\n for(unsigned int t=0; t &tri, const std::vector &x,\n const Vec3f &origin, float dx, int nx, int ny, int nz,\n Array3f &phi, const int exact_band=1);\n\n#endif\n" }, { "path": "Externals/SDFGen/util.h", "content": "#ifndef UTIL_H\n#define UTIL_H\n\n#include \n#include \n#include \n#include \n\n#ifndef M_PI\nconst double M_PI = 3.1415926535897932384626433832795;\n#endif\n\n#ifdef WIN32\n#undef min\n#undef max\n#endif\n\nusing std::min;\nusing std::max;\nusing std::swap;\n\ntemplate\ninline T sqr(const T& x)\n{ return x*x; }\n\ntemplate\ninline T cube(const T& x)\n{ return x*x*x; }\n\ntemplate\ninline T min(T a1, T a2, T a3)\n{ return min(a1, min(a2, a3)); }\n\ntemplate\ninline T min(T a1, T a2, T a3, T a4)\n{ return min(min(a1, a2), min(a3, a4)); }\n\ntemplate\ninline T min(T a1, T a2, T a3, T a4, T a5)\n{ return min(min(a1, a2), min(a3, a4), a5); }\n\ntemplate\ninline T min(T a1, T a2, T a3, T a4, T a5, T a6)\n{ return min(min(a1, a2), min(a3, a4), min(a5, a6)); }\n\ntemplate\ninline T max(T a1, T a2, T a3)\n{ return max(a1, max(a2, a3)); }\n\ntemplate\ninline T max(T a1, T a2, T a3, T a4)\n{ return max(max(a1, a2), max(a3, a4)); }\n\ntemplate\ninline T max(T a1, T a2, T a3, T a4, T a5)\n{ return max(max(a1, a2), max(a3, a4), a5); }\n\ntemplate\ninline T max(T a1, T a2, T a3, T a4, T a5, T a6)\n{ return max(max(a1, a2), max(a3, a4), max(a5, a6)); }\n\ntemplate\ninline void minmax(T a1, T a2, T& amin, T& amax)\n{\n if(a1\ninline void minmax(T a1, T a2, T a3, T& amin, T& amax)\n{\n if(a1\ninline void minmax(T a1, T a2, T a3, T a4, T& amin, T& amax)\n{\n if(a1\ninline void minmax(T a1, T a2, T a3, T a4, T a5, T& amin, T& amax)\n{\n //@@@ the logic could be shortcircuited a lot!\n amin=min(a1,a2,a3,a4,a5);\n amax=max(a1,a2,a3,a4,a5);\n}\n\ntemplate\ninline void minmax(T a1, T a2, T a3, T a4, T a5, T a6, T& amin, T& amax)\n{\n //@@@ the logic could be shortcircuited a lot!\n amin=min(a1,a2,a3,a4,a5,a6);\n amax=max(a1,a2,a3,a4,a5,a6);\n}\n\ntemplate\ninline void update_minmax(T a1, T& amin, T& amax)\n{\n if(a1amax) amax=a1;\n}\n\ntemplate\ninline void sort(T &a, T &b, T &c)\n{\n T temp;\n if(a\ninline T clamp(T a, T lower, T upper)\n{\n if(aupper) return upper;\n else return a;\n}\n\n// only makes sense with T=float or double\ntemplate\ninline T smooth_step(T r)\n{\n if(r<0) return 0;\n else if(r>1) return 1;\n return r*r*r*(10+r*(-15+r*6));\n}\n\n// only makes sense with T=float or double\ntemplate\ninline T smooth_step(T r, T r_lower, T r_upper, T value_lower, T value_upper)\n{ return value_lower + smooth_step((r-r_lower)/(r_upper-r_lower)) * (value_upper-value_lower); }\n\n// only makes sense with T=float or double\ntemplate\ninline T ramp(T r)\n{ return smooth_step((r+1)/2)*2-1; }\n\n#ifdef WIN32\ninline int lround(double x)\n{\n if(x>0)\n return (x-floor(x)<0.5) ? (int)floor(x) : (int)ceil(x);\n else\n return (x-floor(x)<=0.5) ? (int)floor(x) : (int)ceil(x);\n}\n\ninline double remainder(double x, double y)\n{\n return x-std::floor(x/y+0.5)*y;\n}\n#endif\n\ninline unsigned int round_up_to_power_of_two(unsigned int n)\n{\n int exponent=0;\n --n;\n while(n){\n ++exponent;\n n>>=1;\n }\n return 1<1){\n ++exponent;\n n>>=1;\n }\n return 1<>16);\n i*=2654435769u;\n i^=(i>>16);\n i*=2654435769u;\n return i;\n}\n\n// the inverse of randhash\ninline unsigned int unhash(unsigned int h)\n{\n h*=340573321u;\n h^=(h>>16);\n h*=340573321u;\n h^=(h>>16);\n h*=340573321u;\n h^=0xA3C59AC3u;\n return h;\n}\n\n// returns repeatable stateless pseudo-random number in [0,1]\ninline double randhashd(unsigned int seed)\n{ return randhash(seed)/(double)UINT_MAX; }\ninline float randhashf(unsigned int seed)\n{ return randhash(seed)/(float)UINT_MAX; }\n\n// returns repeatable stateless pseudo-random number in [a,b]\ninline double randhashd(unsigned int seed, double a, double b)\n{ return (b-a)*randhash(seed)/(double)UINT_MAX + a; }\ninline float randhashf(unsigned int seed, float a, float b)\n{ return ( (b-a)*randhash(seed)/(float)UINT_MAX + a); }\n\ninline int intlog2(int x)\n{\n int exp=-1;\n while(x){\n x>>=1;\n ++exp;\n }\n return exp;\n}\n\ntemplate\ninline void get_barycentric(T x, int& i, T& f, int i_low, int i_high)\n{\n T s=std::floor(x);\n i=(int)s;\n if(ii_high-2){\n i=i_high-2;\n f=1;\n }else\n f=(T)(x-s);\n}\n\ntemplate\ninline S lerp(const S& value0, const S& value1, T f)\n{ return (1-f)*value0 + f*value1; }\n\ntemplate\ninline S bilerp(const S& v00, const S& v10, \n const S& v01, const S& v11, \n T fx, T fy)\n{ \n return lerp(lerp(v00, v10, fx),\n lerp(v01, v11, fx), \n fy);\n}\n\ntemplate\ninline S trilerp(const S& v000, const S& v100,\n const S& v010, const S& v110,\n const S& v001, const S& v101, \n const S& v011, const S& v111,\n T fx, T fy, T fz) \n{\n return lerp(bilerp(v000, v100, v010, v110, fx, fy),\n bilerp(v001, v101, v011, v111, fx, fy),\n fz);\n}\n\ntemplate\ninline S quadlerp(const S& v0000, const S& v1000,\n const S& v0100, const S& v1100,\n const S& v0010, const S& v1010, \n const S& v0110, const S& v1110,\n const S& v0001, const S& v1001,\n const S& v0101, const S& v1101,\n const S& v0011, const S& v1011, \n const S& v0111, const S& v1111,\n T fx, T fy, T fz, T ft) \n{\n return lerp(trilerp(v0000, v1000, v0100, v1100, v0010, v1010, v0110, v1110, fx, fy, fz),\n trilerp(v0001, v1001, v0101, v1101, v0011, v1011, v0111, v1111, fx, fy, fz),\n ft);\n}\n\n// f should be between 0 and 1, with f=0.5 corresponding to balanced weighting between w0 and w2\ntemplate\ninline void quadratic_bspline_weights(T f, T& w0, T& w1, T& w2)\n{\n w0=T(0.5)*sqr(f-1);\n w1=T(0.75)-sqr(f-T(0.5));;\n w2=T(0.5)*sqr(f);\n}\n\n// f should be between 0 and 1\ntemplate\ninline void cubic_interp_weights(T f, T& wneg1, T& w0, T& w1, T& w2)\n{\n T f2(f*f), f3(f2*f);\n wneg1=-T(1./3)*f+T(1./2)*f2-T(1./6)*f3;\n w0=1-f2+T(1./2)*(f3-f);\n w1=f+T(1./2)*(f2-f3);\n w2=T(1./6)*(f3-f);\n}\n\ntemplate\ninline S cubic_interp(const S& value_neg1, const S& value0, const S& value1, const S& value2, T f)\n{\n T wneg1, w0, w1, w2;\n cubic_interp_weights(f, wneg1, w0, w1, w2);\n return wneg1*value_neg1 + w0*value0 + w1*value1 + w2*value2;\n}\n\ntemplate\nvoid zero(std::vector& v)\n{ for(int i=(int)v.size()-1; i>=0; --i) v[i]=0; }\n\ntemplate\nT abs_max(const std::vector& v)\n{\n T m=0;\n for(int i=(int)v.size()-1; i>=0; --i){\n if(std::fabs(v[i])>m)\n m=std::fabs(v[i]);\n }\n return m;\n}\n\ntemplate\nbool contains(const std::vector& a, T e)\n{\n for(unsigned int i=0; i\nvoid add_unique(std::vector& a, T e)\n{\n for(unsigned int i=0; i\nvoid insert(std::vector& a, unsigned int index, T e)\n{\n a.push_back(a.back());\n for(unsigned int i=(unsigned int)a.size()-1; i>index; --i)\n a[i]=a[i-1];\n a[index]=e;\n}\n\ntemplate\nvoid erase(std::vector& a, unsigned int index)\n{\n for(unsigned int i=index; i\nvoid erase_swap(std::vector& a, unsigned int index)\n{\n for(unsigned int i=index; i\nvoid erase_unordered(std::vector& a, unsigned int index)\n{\n a[index]=a.back();\n a.pop_back();\n}\n\ntemplate\nvoid erase_unordered_swap(std::vector& a, unsigned int index)\n{\n swap(a[index], a.back());\n a.pop_back();\n}\n\ntemplate\nvoid find_and_erase_unordered(std::vector& a, const T& doomed_element)\n{\n for(unsigned int i=0; i\nvoid replace_once(std::vector& a, const T& old_element, const T& new_element)\n{\n for(unsigned int i=0; i\nvoid write_matlab(std::ostream& output, const std::vector& a, const char *variable_name, bool column_vector=true, int significant_digits=18)\n{\n output<\n#include \n#include \n#include \"util.h\"\n\n// Defines a thin wrapper around fixed size C-style arrays, using template parameters,\n// which is useful for dealing with vectors of different dimensions.\n// For example, float[3] is equivalent to Vec<3,float>.\n// Entries in the vector are accessed with the overloaded [] operator, so\n// for example if x is a Vec<3,float>, then the middle entry is x[1].\n// For convenience, there are a number of typedefs for abbreviation:\n// Vec<3,float> -> Vec3f\n// Vec<2,int> -> Vec2i\n// and so on.\n// Arithmetic operators are appropriately overloaded, and functions are defined\n// for additional operations (such as dot-products, norms, cross-products, etc.)\n\ntemplate\nstruct Vec\n{\n T v[N];\n\n Vec(void)\n {}\n\n explicit Vec(T value_for_all)\n { for(unsigned int i=0; i\n explicit Vec(const S *source)\n { for(unsigned int i=0; i\n explicit Vec(const Vec& source)\n { for(unsigned int i=0; i(T v0, T v1)\n {\n assert(N==2);\n v[0]=v0; v[1]=v1;\n }\n\n Vec(T v0, T v1, T v2)\n {\n assert(N==3);\n v[0]=v0; v[1]=v1; v[2]=v2;\n }\n\n Vec(T v0, T v1, T v2, T v3)\n {\n assert(N==4);\n v[0]=v0; v[1]=v1; v[2]=v2; v[3]=v3;\n }\n\n Vec(T v0, T v1, T v2, T v3, T v4)\n {\n assert(N==5);\n v[0]=v0; v[1]=v1; v[2]=v2; v[3]=v3; v[4]=v4;\n }\n\n Vec(T v0, T v1, T v2, T v3, T v4, T v5)\n {\n assert(N==6);\n v[0]=v0; v[1]=v1; v[2]=v2; v[3]=v3; v[4]=v4; v[5]=v5;\n }\n\n T &operator[](int index)\n {\n assert(0<=index && (unsigned int)index operator+=(const Vec &w)\n {\n for(unsigned int i=0; i operator+(const Vec &w) const\n {\n Vec sum(*this);\n sum+=w;\n return sum;\n }\n\n Vec operator-=(const Vec &w)\n {\n for(unsigned int i=0; i operator-(void) const // unary minus\n {\n Vec negative;\n for(unsigned int i=0; i operator-(const Vec &w) const // (binary) subtraction\n {\n Vec diff(*this);\n diff-=w;\n return diff;\n }\n\n Vec operator*=(T a)\n {\n for(unsigned int i=0; i operator*(T a) const\n {\n Vec w(*this);\n w*=a;\n return w;\n }\n\n Vec operator*=(const Vec &w)\n {\n for(unsigned int i=0; i operator*(const Vec &w) const\n {\n Vec componentwise_product;\n for(unsigned int i=0; i operator/=(T a)\n {\n for(unsigned int i=0; i operator/(T a) const\n {\n Vec w(*this);\n w/=a;\n return w;\n }\n};\n\ntypedef Vec<2,double> Vec2d;\ntypedef Vec<2,float> Vec2f;\ntypedef Vec<2,int> Vec2i;\ntypedef Vec<2,unsigned int> Vec2ui;\ntypedef Vec<2,short> Vec2s;\ntypedef Vec<2,unsigned short> Vec2us;\ntypedef Vec<2,char> Vec2c;\ntypedef Vec<2,unsigned char> Vec2uc;\n\ntypedef Vec<3,double> Vec3d;\ntypedef Vec<3,float> Vec3f;\ntypedef Vec<3,int> Vec3i;\ntypedef Vec<3,unsigned int> Vec3ui;\ntypedef Vec<3,short> Vec3s;\ntypedef Vec<3,unsigned short> Vec3us;\ntypedef Vec<3,char> Vec3c;\ntypedef Vec<3,unsigned char> Vec3uc;\n\ntypedef Vec<4,double> Vec4d;\ntypedef Vec<4,float> Vec4f;\ntypedef Vec<4,int> Vec4i;\ntypedef Vec<4,unsigned int> Vec4ui;\ntypedef Vec<4,short> Vec4s;\ntypedef Vec<4,unsigned short> Vec4us;\ntypedef Vec<4,char> Vec4c;\ntypedef Vec<4,unsigned char> Vec4uc;\n\ntypedef Vec<6,double> Vec6d;\ntypedef Vec<6,float> Vec6f;\ntypedef Vec<6,unsigned int> Vec6ui;\ntypedef Vec<6,int> Vec6i;\ntypedef Vec<6,short> Vec6s;\ntypedef Vec<6,unsigned short> Vec6us;\ntypedef Vec<6,char> Vec6c;\ntypedef Vec<6,unsigned char> Vec6uc;\n\n\ntemplate\nT mag2(const Vec &a)\n{\n T l=sqr(a.v[0]);\n for(unsigned int i=1; i\nT mag(const Vec &a)\n{ return sqrt(mag2(a)); }\n\ntemplate \ninline T dist2(const Vec &a, const Vec &b)\n{ \n T d=sqr(a.v[0]-b.v[0]);\n for(unsigned int i=1; i \ninline T dist(const Vec &a, const Vec &b)\n{ return std::sqrt(dist2(a,b)); }\n\ntemplate \ninline void normalize(Vec &a)\n{ a/=mag(a); }\n\ntemplate \ninline Vec normalized(const Vec &a)\n{ return a/mag(a); }\n\ntemplate \ninline T infnorm(const Vec &a)\n{\n T d=std::fabs(a.v[0]);\n for(unsigned int i=1; i\nvoid zero(Vec &a)\n{ \n for(unsigned int i=0; i\nstd::ostream &operator<<(std::ostream &out, const Vec &v)\n{\n out<\nstd::istream &operator>>(std::istream &in, Vec &v)\n{\n in>>v.v[0];\n for(unsigned int i=1; i>v.v[i];\n return in;\n}\n\ntemplate \ninline bool operator==(const Vec &a, const Vec &b)\n{ \n bool t = (a.v[0] == b.v[0]);\n unsigned int i=1;\n while(i \ninline bool operator!=(const Vec &a, const Vec &b)\n{ \n bool t = (a.v[0] != b.v[0]);\n unsigned int i=1;\n while(i\ninline Vec operator*(T a, const Vec &v)\n{\n Vec w(v);\n w*=a;\n return w;\n}\n\ntemplate\ninline T min(const Vec &a)\n{\n T m=a.v[0];\n for(unsigned int i=1; i\ninline Vec min_union(const Vec &a, const Vec &b)\n{\n Vec m;\n for(unsigned int i=0; i\ninline Vec max_union(const Vec &a, const Vec &b)\n{\n Vec m;\n for(unsigned int i=0; i b.v[i]) ? m.v[i]=a.v[i] : m.v[i]=b.v[i];\n return m;\n}\n\ntemplate\ninline T max(const Vec &a)\n{\n T m=a.v[0];\n for(unsigned int i=1; im) m=a.v[i];\n return m;\n}\n\ntemplate\ninline T dot(const Vec &a, const Vec &b)\n{\n T d=a.v[0]*b.v[0];\n for(unsigned int i=1; i \ninline Vec<2,T> rotate(const Vec<2,T>& a, float angle) \n{\n T c = cos(angle);\n T s = sin(angle);\n return Vec<2,T>(c*a[0] - s*a[1],s*a[0] + c*a[1]); // counter-clockwise rotation\n}\n\ntemplate\ninline Vec<2,T> perp(const Vec<2,T> &a)\n{ return Vec<2,T>(-a.v[1], a.v[0]); } // counter-clockwise rotation by 90 degrees\n\ntemplate\ninline T cross(const Vec<2,T> &a, const Vec<2,T> &b)\n{ return a.v[0]*b.v[1]-a.v[1]*b.v[0]; }\n\ntemplate\ninline Vec<3,T> cross(const Vec<3,T> &a, const Vec<3,T> &b)\n{ return Vec<3,T>(a.v[1]*b.v[2]-a.v[2]*b.v[1], a.v[2]*b.v[0]-a.v[0]*b.v[2], a.v[0]*b.v[1]-a.v[1]*b.v[0]); }\n\ntemplate\ninline T triple(const Vec<3,T> &a, const Vec<3,T> &b, const Vec<3,T> &c)\n{ return a.v[0]*(b.v[1]*c.v[2]-b.v[2]*c.v[1])\n +a.v[1]*(b.v[2]*c.v[0]-b.v[0]*c.v[2])\n +a.v[2]*(b.v[0]*c.v[1]-b.v[1]*c.v[0]); }\n\ntemplate\ninline unsigned int hash(const Vec &a)\n{\n unsigned int h=a.v[0];\n for(unsigned int i=1; i\ninline void assign(const Vec &a, T &a0, T &a1)\n{ \n assert(N==2);\n a0=a.v[0]; a1=a.v[1];\n}\n\ntemplate\ninline void assign(const Vec &a, T &a0, T &a1, T &a2)\n{ \n assert(N==3);\n a0=a.v[0]; a1=a.v[1]; a2=a.v[2];\n}\n\ntemplate\ninline void assign(const Vec &a, T &a0, T &a1, T &a2, T &a3)\n{ \n assert(N==4);\n a0=a.v[0]; a1=a.v[1]; a2=a.v[2]; a3=a.v[3];\n}\n\ntemplate\ninline void assign(const Vec &a, T &a0, T &a1, T &a2, T &a3, T &a4, T &a5)\n{ \n assert(N==6);\n a0=a.v[0]; a1=a.v[1]; a2=a.v[2]; a3=a.v[3]; a4=a.v[4]; a5=a.v[5];\n}\n\ntemplate\ninline Vec round(const Vec &a)\n{ \n Vec rounded;\n for(unsigned int i=0; i\ninline Vec floor(const Vec &a)\n{ \n Vec rounded;\n for(unsigned int i=0; i\ninline Vec ceil(const Vec &a)\n{ \n Vec rounded;\n for(unsigned int i=0; i\ninline Vec fabs(const Vec &a)\n{ \n Vec result;\n for(unsigned int i=0; i\ninline void minmax(const Vec &x0, const Vec &x1, Vec &xmin, Vec &xmax)\n{\n for(unsigned int i=0; i\ninline void minmax(const Vec &x0, const Vec &x1, const Vec &x2, Vec &xmin, Vec &xmax)\n{\n for(unsigned int i=0; i\ninline void minmax(const Vec &x0, const Vec &x1, const Vec &x2, const Vec &x3,\n Vec &xmin, Vec &xmax)\n{\n for(unsigned int i=0; i\ninline void minmax(const Vec &x0, const Vec &x1, const Vec &x2, const Vec &x3, const Vec &x4,\n Vec &xmin, Vec &xmax)\n{\n for(unsigned int i=0; i\ninline void minmax(const Vec &x0, const Vec &x1, const Vec &x2, const Vec &x3, const Vec &x4,\n const Vec &x5, Vec &xmin, Vec &xmax)\n{\n for(unsigned int i=0; i\ninline void update_minmax(const Vec &x, Vec &xmin, Vec &xmax)\n{\n for(unsigned int i=0; i.\n///\n\n#ifndef TL_FUNCTION_REF_HPP\n#define TL_FUNCTION_REF_HPP\n\n#define TL_FUNCTION_REF_VERSION_MAJOR 1\n#define TL_FUNCTION_REF_VERSION_MINOR 0\n#define TL_FUNCTION_REF_VERSION_PATCH 0\n\n#if (defined(_MSC_VER) && _MSC_VER == 1900)\n/// \\exclude\n#define TL_FUNCTION_REF_MSVC2015\n#endif\n\n#if (defined(__GNUC__) && __GNUC__ == 4 && __GNUC_MINOR__ <= 9 && \\\n !defined(__clang__))\n/// \\exclude\n#define TL_FUNCTION_REF_GCC49\n#endif\n\n#if (defined(__GNUC__) && __GNUC__ == 5 && __GNUC_MINOR__ <= 4 && \\\n !defined(__clang__))\n/// \\exclude\n#define TL_FUNCTION_REF_GCC54\n#endif\n\n#if (defined(__GNUC__) && __GNUC__ == 4 && __GNUC_MINOR__ <= 9 && \\\n !defined(__clang__))\n// GCC < 5 doesn't support overloading on const&& for member functions\n/// \\exclude\n#define TL_FUNCTION_REF_NO_CONSTRR\n#endif\n\n#if __cplusplus > 201103L\n/// \\exclude\n#define TL_FUNCTION_REF_CXX14\n#endif\n\n// constexpr implies const in C++11, not C++14\n#if (__cplusplus == 201103L || defined(TL_FUNCTION_REF_MSVC2015) || \\\n defined(TL_FUNCTION_REF_GCC49)) && \\\n !defined(TL_FUNCTION_REF_GCC54)\n/// \\exclude\n#define TL_FUNCTION_REF_11_CONSTEXPR\n#else\n/// \\exclude\n#define TL_FUNCTION_REF_11_CONSTEXPR constexpr\n#endif\n\n#include \n#include \n\nnamespace tl {\nnamespace detail {\nnamespace fnref {\n// C++14-style aliases for brevity\ntemplate using remove_const_t = typename std::remove_const::type;\ntemplate \nusing remove_reference_t = typename std::remove_reference::type;\ntemplate using decay_t = typename std::decay::type;\ntemplate \nusing enable_if_t = typename std::enable_if::type;\ntemplate \nusing conditional_t = typename std::conditional::type;\n\n// std::invoke from C++17\n// https://stackoverflow.com/questions/38288042/c11-14-invoke-workaround\ntemplate >::value>,\n int = 0>\nconstexpr auto invoke(Fn &&f, Args &&... args) noexcept(\n noexcept(std::mem_fn(f)(std::forward(args)...)))\n -> decltype(std::mem_fn(f)(std::forward(args)...)) {\n return std::mem_fn(f)(std::forward(args)...);\n}\n\ntemplate >{}>>\nconstexpr auto invoke(Fn &&f, Args &&... args) noexcept(\n noexcept(std::forward(f)(std::forward(args)...)))\n -> decltype(std::forward(f)(std::forward(args)...)) {\n return std::forward(f)(std::forward(args)...);\n}\n\n// std::invoke_result from C++17\ntemplate struct invoke_result_impl;\n\ntemplate \nstruct invoke_result_impl<\n F, decltype(tl::detail::fnref::invoke(std::declval(), std::declval()...), void()),\n Us...> {\n using type = decltype(tl::detail::fnref::invoke(std::declval(), std::declval()...));\n};\n\ntemplate \nusing invoke_result = invoke_result_impl;\n\ntemplate \nusing invoke_result_t = typename invoke_result::type;\n\ntemplate \nstruct is_invocable_r_impl : std::false_type {};\n\ntemplate \nstruct is_invocable_r_impl<\n typename std::is_convertible, R>::type, R, F, Args...>\n : std::true_type {};\n\ntemplate \nusing is_invocable_r = is_invocable_r_impl;\n\n} // namespace detail\n} // namespace fnref\n\n/// A lightweight non-owning reference to a callable.\n///\n/// Example usage:\n///\n/// ```cpp\n/// void foo (function_ref func) {\n/// std::cout << \"Result is \" << func(21); //42\n/// }\n///\n/// foo([](int i) { return i*2; });\ntemplate class function_ref;\n\n/// Specialization for function types.\ntemplate class function_ref {\npublic:\n constexpr function_ref() noexcept = delete;\n\n /// Creates a `function_ref` which refers to the same callable as `rhs`.\n constexpr function_ref(const function_ref &rhs) noexcept = default;\n\n /// Constructs a `function_ref` referring to `f`.\n ///\n /// \\synopsis template constexpr function_ref(F &&f) noexcept\n template , function_ref>::value &&\n detail::fnref::is_invocable_r::value> * = nullptr>\n TL_FUNCTION_REF_11_CONSTEXPR function_ref(F &&f) noexcept\n : obj_(const_cast(reinterpret_cast(std::addressof(f)))) {\n callback_ = [](void *obj, Args... args) -> R {\n return detail::fnref::invoke(\n *reinterpret_cast::type>(obj),\n std::forward(args)...);\n };\n }\n\n /// Makes `*this` refer to the same callable as `rhs`.\n TL_FUNCTION_REF_11_CONSTEXPR function_ref &\n operator=(const function_ref &rhs) noexcept = default;\n\n /// Makes `*this` refer to `f`.\n ///\n /// \\synopsis template constexpr function_ref &operator=(F &&f) noexcept;\n template ::value>\n * = nullptr>\n TL_FUNCTION_REF_11_CONSTEXPR function_ref &operator=(F &&f) noexcept {\n obj_ = reinterpret_cast(std::addressof(f));\n callback_ = [](void *obj, Args... args) {\n return detail::fnref::invoke(\n *reinterpret_cast::type>(obj),\n std::forward(args)...);\n };\n\n return *this;\n }\n\n /// Swaps the referred callables of `*this` and `rhs`.\n constexpr void swap(function_ref &rhs) noexcept {\n std::swap(obj_, rhs.obj_);\n std::swap(callback_, rhs.callback_);\n }\n\n /// Call the stored callable with the given arguments.\n R operator()(Args... args) const {\n return callback_(obj_, std::forward(args)...);\n }\n\nprivate:\n void *obj_ = nullptr;\n R (*callback_)(void *, Args...) = nullptr;\n};\n\n/// Swaps the referred callables of `lhs` and `rhs`.\ntemplate \nconstexpr void swap(function_ref &lhs,\n function_ref &rhs) noexcept {\n lhs.swap(rhs);\n}\n\n#if __cplusplus >= 201703L\ntemplate \nfunction_ref(R (*)(Args...))->function_ref;\n\n// TODO, will require some kind of callable traits\n// template \n// function_ref(F) -> function_ref;\n#endif\n} // namespace tl\n\n#endif\n" }, { "path": "Externals/optional/tl/optional.hpp", "content": "\n///\n// optional - An implementation of std::optional with extensions\n// Written in 2017 by Simon Brand (simonrbrand@gmail.com, @TartanLlama)\n//\n// Documentation available at https://tl.tartanllama.xyz/\n//\n// To the extent possible under law, the author(s) have dedicated all\n// copyright and related and neighboring rights to this software to the\n// public domain worldwide. This software is distributed without any warranty.\n//\n// You should have received a copy of the CC0 Public Domain Dedication\n// along with this software. If not, see\n// .\n///\n\n#ifndef TL_OPTIONAL_HPP\n#define TL_OPTIONAL_HPP\n\n#define TL_OPTIONAL_VERSION_MAJOR 1\n#define TL_OPTIONAL_VERSION_MINOR 0\n#define TL_OPTIONAL_VERSION_PATCH 0\n\n#include \n#include \n#include \n#include \n#include \n\n#if (defined(_MSC_VER) && _MSC_VER == 1900)\n#define TL_OPTIONAL_MSVC2015\n#endif\n\n#if (defined(__GNUC__) && __GNUC__ == 4 && __GNUC_MINOR__ <= 9 && \\\n !defined(__clang__))\n#define TL_OPTIONAL_GCC49\n#endif\n\n#if (defined(__GNUC__) && __GNUC__ == 5 && __GNUC_MINOR__ <= 4 && \\\n !defined(__clang__))\n#define TL_OPTIONAL_GCC54\n#endif\n\n#if (defined(__GNUC__) && __GNUC__ == 5 && __GNUC_MINOR__ <= 5 && \\\n !defined(__clang__))\n#define TL_OPTIONAL_GCC55\n#endif\n\n#if (defined(__GNUC__) && __GNUC__ == 4 && __GNUC_MINOR__ <= 9 && \\\n !defined(__clang__))\n// GCC < 5 doesn't support overloading on const&& for member functions\n#define TL_OPTIONAL_NO_CONSTRR\n\n// GCC < 5 doesn't support some standard C++11 type traits\n#define TL_OPTIONAL_IS_TRIVIALLY_COPY_CONSTRUCTIBLE(T) \\\n std::has_trivial_copy_constructor::value\n#define TL_OPTIONAL_IS_TRIVIALLY_COPY_ASSIGNABLE(T) std::has_trivial_copy_assign::value\n\n// This one will be different for GCC 5.7 if it's ever supported\n#define TL_OPTIONAL_IS_TRIVIALLY_DESTRUCTIBLE(T) std::is_trivially_destructible::value\n\n// GCC 5 < v < 8 has a bug in is_trivially_copy_constructible which breaks std::vector\n// for non-copyable types\n#elif (defined(__GNUC__) && __GNUC__ < 8 && \\\n !defined(__clang__))\n#ifndef TL_GCC_LESS_8_TRIVIALLY_COPY_CONSTRUCTIBLE_MUTEX\n#define TL_GCC_LESS_8_TRIVIALLY_COPY_CONSTRUCTIBLE_MUTEX\nnamespace tl {\n namespace detail {\n template\n struct is_trivially_copy_constructible : std::is_trivially_copy_constructible{};\n#ifdef _GLIBCXX_VECTOR\n template\n struct is_trivially_copy_constructible>\n : std::is_trivially_copy_constructible{};\n#endif \n }\n}\n#endif\n\n#define TL_OPTIONAL_IS_TRIVIALLY_COPY_CONSTRUCTIBLE(T) \\\n tl::detail::is_trivially_copy_constructible::value\n#define TL_OPTIONAL_IS_TRIVIALLY_COPY_ASSIGNABLE(T) \\\n std::is_trivially_copy_assignable::value\n#define TL_OPTIONAL_IS_TRIVIALLY_DESTRUCTIBLE(T) std::is_trivially_destructible::value\n#else\n#define TL_OPTIONAL_IS_TRIVIALLY_COPY_CONSTRUCTIBLE(T) \\\n std::is_trivially_copy_constructible::value\n#define TL_OPTIONAL_IS_TRIVIALLY_COPY_ASSIGNABLE(T) \\\n std::is_trivially_copy_assignable::value\n#define TL_OPTIONAL_IS_TRIVIALLY_DESTRUCTIBLE(T) std::is_trivially_destructible::value\n#endif\n\n#if __cplusplus > 201103L\n#define TL_OPTIONAL_CXX14\n#endif\n\n// constexpr implies const in C++11, not C++14\n#if (__cplusplus == 201103L || defined(TL_OPTIONAL_MSVC2015) || \\\n defined(TL_OPTIONAL_GCC49))\n#define TL_OPTIONAL_11_CONSTEXPR\n#else\n#define TL_OPTIONAL_11_CONSTEXPR constexpr\n#endif\n\nnamespace tl {\n#ifndef TL_MONOSTATE_INPLACE_MUTEX\n#define TL_MONOSTATE_INPLACE_MUTEX\n/// Used to represent an optional with no data; essentially a bool\nclass monostate {};\n\n/// A tag type to tell optional to construct its value in-place\nstruct in_place_t {\n explicit in_place_t() = default;\n};\n/// A tag to tell optional to construct its value in-place\nstatic constexpr in_place_t in_place{};\n#endif\n\ntemplate class optional;\n\nnamespace detail {\n#ifndef TL_TRAITS_MUTEX\n#define TL_TRAITS_MUTEX\n// C++14-style aliases for brevity\ntemplate using remove_const_t = typename std::remove_const::type;\ntemplate \nusing remove_reference_t = typename std::remove_reference::type;\ntemplate using decay_t = typename std::decay::type;\ntemplate \nusing enable_if_t = typename std::enable_if::type;\ntemplate \nusing conditional_t = typename std::conditional::type;\n\n// std::conjunction from C++17\ntemplate struct conjunction : std::true_type {};\ntemplate struct conjunction : B {};\ntemplate \nstruct conjunction\n : std::conditional, B>::type {};\n\n#if defined(_LIBCPP_VERSION) && __cplusplus == 201103L\n#define TL_TRAITS_LIBCXX_MEM_FN_WORKAROUND\n#endif\n\n// In C++11 mode, there's an issue in libc++'s std::mem_fn\n// which results in a hard-error when using it in a noexcept expression\n// in some cases. This is a check to workaround the common failing case.\n#ifdef TL_TRAITS_LIBCXX_MEM_FN_WORKAROUND\ntemplate struct is_pointer_to_non_const_member_func : std::false_type{};\ntemplate \nstruct is_pointer_to_non_const_member_func : std::true_type{};\ntemplate \nstruct is_pointer_to_non_const_member_func : std::true_type{};\ntemplate \nstruct is_pointer_to_non_const_member_func : std::true_type{}; \ntemplate \nstruct is_pointer_to_non_const_member_func : std::true_type{};\ntemplate \nstruct is_pointer_to_non_const_member_func : std::true_type{};\ntemplate \nstruct is_pointer_to_non_const_member_func : std::true_type{}; \n\ntemplate struct is_const_or_const_ref : std::false_type{};\ntemplate struct is_const_or_const_ref : std::true_type{};\ntemplate struct is_const_or_const_ref : std::true_type{}; \n#endif\n\n// std::invoke from C++17\n// https://stackoverflow.com/questions/38288042/c11-14-invoke-workaround\ntemplate ::value \n && is_const_or_const_ref::value)>, \n#endif\n typename = enable_if_t>::value>,\n int = 0>\nconstexpr auto invoke(Fn &&f, Args &&... args) noexcept(\n noexcept(std::mem_fn(f)(std::forward(args)...)))\n -> decltype(std::mem_fn(f)(std::forward(args)...)) {\n return std::mem_fn(f)(std::forward(args)...);\n}\n\ntemplate >::value>>\nconstexpr auto invoke(Fn &&f, Args &&... args) noexcept(\n noexcept(std::forward(f)(std::forward(args)...)))\n -> decltype(std::forward(f)(std::forward(args)...)) {\n return std::forward(f)(std::forward(args)...);\n}\n\n// std::invoke_result from C++17\ntemplate struct invoke_result_impl;\n\ntemplate \nstruct invoke_result_impl<\n F, decltype(detail::invoke(std::declval(), std::declval()...), void()),\n Us...> {\n using type = decltype(detail::invoke(std::declval(), std::declval()...));\n};\n\ntemplate \nusing invoke_result = invoke_result_impl;\n\ntemplate \nusing invoke_result_t = typename invoke_result::type;\n\n#if defined(_MSC_VER) && _MSC_VER <= 1900\n// TODO make a version which works with MSVC 2015\ntemplate struct is_swappable : std::true_type {};\n\ntemplate struct is_nothrow_swappable : std::true_type {};\n#else\n// https://stackoverflow.com/questions/26744589/what-is-a-proper-way-to-implement-is-swappable-to-test-for-the-swappable-concept\nnamespace swap_adl_tests {\n// if swap ADL finds this then it would call std::swap otherwise (same\n// signature)\nstruct tag {};\n\ntemplate tag swap(T &, T &);\ntemplate tag swap(T (&a)[N], T (&b)[N]);\n\n// helper functions to test if an unqualified swap is possible, and if it\n// becomes std::swap\ntemplate std::false_type can_swap(...) noexcept(false);\ntemplate (), std::declval()))>\nstd::true_type can_swap(int) noexcept(noexcept(swap(std::declval(),\n std::declval())));\n\ntemplate std::false_type uses_std(...);\ntemplate \nstd::is_same(), std::declval())), tag>\nuses_std(int);\n\ntemplate \nstruct is_std_swap_noexcept\n : std::integral_constant::value &&\n std::is_nothrow_move_assignable::value> {};\n\ntemplate \nstruct is_std_swap_noexcept : is_std_swap_noexcept {};\n\ntemplate \nstruct is_adl_swap_noexcept\n : std::integral_constant(0))> {};\n} // namespace swap_adl_tests\n\ntemplate \nstruct is_swappable\n : std::integral_constant<\n bool,\n decltype(detail::swap_adl_tests::can_swap(0))::value &&\n (!decltype(detail::swap_adl_tests::uses_std(0))::value ||\n (std::is_move_assignable::value &&\n std::is_move_constructible::value))> {};\n\ntemplate \nstruct is_swappable\n : std::integral_constant<\n bool,\n decltype(detail::swap_adl_tests::can_swap(0))::value &&\n (!decltype(\n detail::swap_adl_tests::uses_std(0))::value ||\n is_swappable::value)> {};\n\ntemplate \nstruct is_nothrow_swappable\n : std::integral_constant<\n bool,\n is_swappable::value &&\n ((decltype(detail::swap_adl_tests::uses_std(0))::value\n &&detail::swap_adl_tests::is_std_swap_noexcept::value) ||\n (!decltype(detail::swap_adl_tests::uses_std(0))::value &&\n detail::swap_adl_tests::is_adl_swap_noexcept::value))> {\n};\n#endif\n#endif\n\n// std::void_t from C++17\ntemplate struct voider { using type = void; };\ntemplate using void_t = typename voider::type;\n\n// Trait for checking if a type is a tl::optional\ntemplate struct is_optional_impl : std::false_type {};\ntemplate struct is_optional_impl> : std::true_type {};\ntemplate using is_optional = is_optional_impl>;\n\n// Change void to tl::monostate\ntemplate \nusing fixup_void = conditional_t::value, monostate, U>;\n\ntemplate >\nusing get_map_return = optional>>;\n\n// Check if invoking F for some Us returns void\ntemplate struct returns_void_impl;\ntemplate \nstruct returns_void_impl>, U...>\n : std::is_void> {};\ntemplate \nusing returns_void = returns_void_impl;\n\ntemplate \nusing enable_if_ret_void = enable_if_t::value>;\n\ntemplate \nusing disable_if_ret_void = enable_if_t::value>;\n\ntemplate \nusing enable_forward_value =\n detail::enable_if_t::value &&\n !std::is_same, in_place_t>::value &&\n !std::is_same, detail::decay_t>::value>;\n\ntemplate \nusing enable_from_other = detail::enable_if_t<\n std::is_constructible::value &&\n !std::is_constructible &>::value &&\n !std::is_constructible &&>::value &&\n !std::is_constructible &>::value &&\n !std::is_constructible &&>::value &&\n !std::is_convertible &, T>::value &&\n !std::is_convertible &&, T>::value &&\n !std::is_convertible &, T>::value &&\n !std::is_convertible &&, T>::value>;\n\ntemplate \nusing enable_assign_forward = detail::enable_if_t<\n !std::is_same, detail::decay_t>::value &&\n !detail::conjunction,\n std::is_same>>::value &&\n std::is_constructible::value && std::is_assignable::value>;\n\ntemplate \nusing enable_assign_from_other = detail::enable_if_t<\n std::is_constructible::value &&\n std::is_assignable::value &&\n !std::is_constructible &>::value &&\n !std::is_constructible &&>::value &&\n !std::is_constructible &>::value &&\n !std::is_constructible &&>::value &&\n !std::is_convertible &, T>::value &&\n !std::is_convertible &&, T>::value &&\n !std::is_convertible &, T>::value &&\n !std::is_convertible &&, T>::value &&\n !std::is_assignable &>::value &&\n !std::is_assignable &&>::value &&\n !std::is_assignable &>::value &&\n !std::is_assignable &&>::value>;\n\n// The storage base manages the actual storage, and correctly propagates\n// trivial destruction from T. This case is for when T is not trivially\n// destructible.\ntemplate ::value>\nstruct optional_storage_base {\n TL_OPTIONAL_11_CONSTEXPR optional_storage_base() noexcept\n : m_dummy(), m_has_value(false) {}\n\n template \n TL_OPTIONAL_11_CONSTEXPR optional_storage_base(in_place_t, U &&... u)\n : m_value(std::forward(u)...), m_has_value(true) {}\n\n ~optional_storage_base() {\n if (m_has_value) {\n m_value.~T();\n m_has_value = false;\n }\n }\n\n struct dummy {};\n union {\n dummy m_dummy;\n T m_value;\n };\n\n bool m_has_value;\n};\n\n// This case is for when T is trivially destructible.\ntemplate struct optional_storage_base {\n TL_OPTIONAL_11_CONSTEXPR optional_storage_base() noexcept\n : m_dummy(), m_has_value(false) {}\n\n template \n TL_OPTIONAL_11_CONSTEXPR optional_storage_base(in_place_t, U &&... u)\n : m_value(std::forward(u)...), m_has_value(true) {}\n\n // No destructor, so this class is trivially destructible\n\n struct dummy {};\n union {\n dummy m_dummy;\n T m_value;\n };\n\n bool m_has_value = false;\n};\n\n// This base class provides some handy member functions which can be used in\n// further derived classes\ntemplate struct optional_operations_base : optional_storage_base {\n using optional_storage_base::optional_storage_base;\n\n void hard_reset() noexcept {\n get().~T();\n this->m_has_value = false;\n }\n\n template void construct(Args &&... args) noexcept {\n new (std::addressof(this->m_value)) T(std::forward(args)...);\n this->m_has_value = true;\n }\n\n template void assign(Opt &&rhs) {\n if (this->has_value()) {\n if (rhs.has_value()) {\n this->m_value = std::forward(rhs).get();\n } else {\n this->m_value.~T();\n this->m_has_value = false;\n }\n }\n\n else if (rhs.has_value()) {\n construct(std::forward(rhs).get());\n }\n }\n\n bool has_value() const { return this->m_has_value; }\n\n TL_OPTIONAL_11_CONSTEXPR T &get() & { return this->m_value; }\n TL_OPTIONAL_11_CONSTEXPR const T &get() const & { return this->m_value; }\n TL_OPTIONAL_11_CONSTEXPR T &&get() && { return std::move(this->m_value); }\n#ifndef TL_OPTIONAL_NO_CONSTRR\n constexpr const T &&get() const && { return std::move(this->m_value); }\n#endif\n};\n\n// This class manages conditionally having a trivial copy constructor\n// This specialization is for when T is trivially copy constructible\ntemplate \nstruct optional_copy_base : optional_operations_base {\n using optional_operations_base::optional_operations_base;\n};\n\n// This specialization is for when T is not trivially copy constructible\ntemplate \nstruct optional_copy_base : optional_operations_base {\n using optional_operations_base::optional_operations_base;\n\n optional_copy_base() = default;\n optional_copy_base(const optional_copy_base &rhs) {\n if (rhs.has_value()) {\n this->construct(rhs.get());\n } else {\n this->m_has_value = false;\n }\n }\n\n optional_copy_base(optional_copy_base &&rhs) = default;\n optional_copy_base &operator=(const optional_copy_base &rhs) = default;\n optional_copy_base &operator=(optional_copy_base &&rhs) = default;\n};\n\n// This class manages conditionally having a trivial move constructor\n// Unfortunately there's no way to achieve this in GCC < 5 AFAIK, since it\n// doesn't implement an analogue to std::is_trivially_move_constructible. We\n// have to make do with a non-trivial move constructor even if T is trivially\n// move constructible\n#ifndef TL_OPTIONAL_GCC49\ntemplate ::value>\nstruct optional_move_base : optional_copy_base {\n using optional_copy_base::optional_copy_base;\n};\n#else\ntemplate struct optional_move_base;\n#endif\ntemplate struct optional_move_base : optional_copy_base {\n using optional_copy_base::optional_copy_base;\n\n optional_move_base() = default;\n optional_move_base(const optional_move_base &rhs) = default;\n\n optional_move_base(optional_move_base &&rhs) noexcept(\n std::is_nothrow_move_constructible::value) {\n if (rhs.has_value()) {\n this->construct(std::move(rhs.get()));\n } else {\n this->m_has_value = false;\n }\n }\n optional_move_base &operator=(const optional_move_base &rhs) = default;\n optional_move_base &operator=(optional_move_base &&rhs) = default;\n};\n\n// This class manages conditionally having a trivial copy assignment operator\ntemplate \nstruct optional_copy_assign_base : optional_move_base {\n using optional_move_base::optional_move_base;\n};\n\ntemplate \nstruct optional_copy_assign_base : optional_move_base {\n using optional_move_base::optional_move_base;\n\n optional_copy_assign_base() = default;\n optional_copy_assign_base(const optional_copy_assign_base &rhs) = default;\n\n optional_copy_assign_base(optional_copy_assign_base &&rhs) = default;\n optional_copy_assign_base &operator=(const optional_copy_assign_base &rhs) {\n this->assign(rhs);\n return *this;\n }\n optional_copy_assign_base &\n operator=(optional_copy_assign_base &&rhs) = default;\n};\n\n// This class manages conditionally having a trivial move assignment operator\n// Unfortunately there's no way to achieve this in GCC < 5 AFAIK, since it\n// doesn't implement an analogue to std::is_trivially_move_assignable. We have\n// to make do with a non-trivial move assignment operator even if T is trivially\n// move assignable\n#ifndef TL_OPTIONAL_GCC49\ntemplate ::value\n &&std::is_trivially_move_constructible::value\n &&std::is_trivially_move_assignable::value>\nstruct optional_move_assign_base : optional_copy_assign_base {\n using optional_copy_assign_base::optional_copy_assign_base;\n};\n#else\ntemplate struct optional_move_assign_base;\n#endif\n\ntemplate \nstruct optional_move_assign_base : optional_copy_assign_base {\n using optional_copy_assign_base::optional_copy_assign_base;\n\n optional_move_assign_base() = default;\n optional_move_assign_base(const optional_move_assign_base &rhs) = default;\n\n optional_move_assign_base(optional_move_assign_base &&rhs) = default;\n\n optional_move_assign_base &\n operator=(const optional_move_assign_base &rhs) = default;\n\n optional_move_assign_base &\n operator=(optional_move_assign_base &&rhs) noexcept(\n std::is_nothrow_move_constructible::value\n &&std::is_nothrow_move_assignable::value) {\n this->assign(std::move(rhs));\n return *this;\n }\n};\n\n// optional_delete_ctor_base will conditionally delete copy and move\n// constructors depending on whether T is copy/move constructible\ntemplate ::value,\n bool EnableMove = std::is_move_constructible::value>\nstruct optional_delete_ctor_base {\n optional_delete_ctor_base() = default;\n optional_delete_ctor_base(const optional_delete_ctor_base &) = default;\n optional_delete_ctor_base(optional_delete_ctor_base &&) noexcept = default;\n optional_delete_ctor_base &\n operator=(const optional_delete_ctor_base &) = default;\n optional_delete_ctor_base &\n operator=(optional_delete_ctor_base &&) noexcept = default;\n};\n\ntemplate struct optional_delete_ctor_base {\n optional_delete_ctor_base() = default;\n optional_delete_ctor_base(const optional_delete_ctor_base &) = default;\n optional_delete_ctor_base(optional_delete_ctor_base &&) noexcept = delete;\n optional_delete_ctor_base &\n operator=(const optional_delete_ctor_base &) = default;\n optional_delete_ctor_base &\n operator=(optional_delete_ctor_base &&) noexcept = default;\n};\n\ntemplate struct optional_delete_ctor_base {\n optional_delete_ctor_base() = default;\n optional_delete_ctor_base(const optional_delete_ctor_base &) = delete;\n optional_delete_ctor_base(optional_delete_ctor_base &&) noexcept = default;\n optional_delete_ctor_base &\n operator=(const optional_delete_ctor_base &) = default;\n optional_delete_ctor_base &\n operator=(optional_delete_ctor_base &&) noexcept = default;\n};\n\ntemplate struct optional_delete_ctor_base {\n optional_delete_ctor_base() = default;\n optional_delete_ctor_base(const optional_delete_ctor_base &) = delete;\n optional_delete_ctor_base(optional_delete_ctor_base &&) noexcept = delete;\n optional_delete_ctor_base &\n operator=(const optional_delete_ctor_base &) = default;\n optional_delete_ctor_base &\n operator=(optional_delete_ctor_base &&) noexcept = default;\n};\n\n// optional_delete_assign_base will conditionally delete copy and move\n// constructors depending on whether T is copy/move constructible + assignable\ntemplate ::value &&\n std::is_copy_assignable::value),\n bool EnableMove = (std::is_move_constructible::value &&\n std::is_move_assignable::value)>\nstruct optional_delete_assign_base {\n optional_delete_assign_base() = default;\n optional_delete_assign_base(const optional_delete_assign_base &) = default;\n optional_delete_assign_base(optional_delete_assign_base &&) noexcept =\n default;\n optional_delete_assign_base &\n operator=(const optional_delete_assign_base &) = default;\n optional_delete_assign_base &\n operator=(optional_delete_assign_base &&) noexcept = default;\n};\n\ntemplate struct optional_delete_assign_base {\n optional_delete_assign_base() = default;\n optional_delete_assign_base(const optional_delete_assign_base &) = default;\n optional_delete_assign_base(optional_delete_assign_base &&) noexcept =\n default;\n optional_delete_assign_base &\n operator=(const optional_delete_assign_base &) = default;\n optional_delete_assign_base &\n operator=(optional_delete_assign_base &&) noexcept = delete;\n};\n\ntemplate struct optional_delete_assign_base {\n optional_delete_assign_base() = default;\n optional_delete_assign_base(const optional_delete_assign_base &) = default;\n optional_delete_assign_base(optional_delete_assign_base &&) noexcept =\n default;\n optional_delete_assign_base &\n operator=(const optional_delete_assign_base &) = delete;\n optional_delete_assign_base &\n operator=(optional_delete_assign_base &&) noexcept = default;\n};\n\ntemplate struct optional_delete_assign_base {\n optional_delete_assign_base() = default;\n optional_delete_assign_base(const optional_delete_assign_base &) = default;\n optional_delete_assign_base(optional_delete_assign_base &&) noexcept =\n default;\n optional_delete_assign_base &\n operator=(const optional_delete_assign_base &) = delete;\n optional_delete_assign_base &\n operator=(optional_delete_assign_base &&) noexcept = delete;\n};\n\n} // namespace detail\n\n/// A tag type to represent an empty optional\nstruct nullopt_t {\n struct do_not_use {};\n constexpr explicit nullopt_t(do_not_use, do_not_use) noexcept {}\n};\n/// Represents an empty optional\nstatic constexpr nullopt_t nullopt{nullopt_t::do_not_use{},\n nullopt_t::do_not_use{}};\n\nclass bad_optional_access : public std::exception {\npublic:\n bad_optional_access() = default;\n const char *what() const noexcept { return \"Optional has no value\"; }\n};\n\n/// An optional object is an object that contains the storage for another\n/// object and manages the lifetime of this contained object, if any. The\n/// contained object may be initialized after the optional object has been\n/// initialized, and may be destroyed before the optional object has been\n/// destroyed. The initialization state of the contained object is tracked by\n/// the optional object.\ntemplate \nclass optional : private detail::optional_move_assign_base,\n private detail::optional_delete_ctor_base,\n private detail::optional_delete_assign_base {\n using base = detail::optional_move_assign_base;\n\n static_assert(!std::is_same::value,\n \"instantiation of optional with in_place_t is ill-formed\");\n static_assert(!std::is_same, nullopt_t>::value,\n \"instantiation of optional with nullopt_t is ill-formed\");\n\npublic:\n// The different versions for C++14 and 11 are needed because deduced return\n// types are not SFINAE-safe. This provides better support for things like\n// generic lambdas. C.f.\n// http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2017/p0826r0.html\n#if defined(TL_OPTIONAL_CXX14) && !defined(TL_OPTIONAL_GCC49) && \\\n !defined(TL_OPTIONAL_GCC54) && !defined(TL_OPTIONAL_GCC55)\n /// Carries out some operation which returns an optional on the stored\n /// object if there is one.\n template TL_OPTIONAL_11_CONSTEXPR auto and_then(F &&f) & {\n using result = detail::invoke_result_t;\n static_assert(detail::is_optional::value,\n \"F must return an optional\");\n\n return has_value() ? detail::invoke(std::forward(f), **this)\n : result(nullopt);\n }\n\n template TL_OPTIONAL_11_CONSTEXPR auto and_then(F &&f) && {\n using result = detail::invoke_result_t;\n static_assert(detail::is_optional::value,\n \"F must return an optional\");\n\n return has_value() ? detail::invoke(std::forward(f), std::move(**this))\n : result(nullopt);\n }\n\n template constexpr auto and_then(F &&f) const & {\n using result = detail::invoke_result_t;\n static_assert(detail::is_optional::value,\n \"F must return an optional\");\n\n return has_value() ? detail::invoke(std::forward(f), **this)\n : result(nullopt);\n }\n\n#ifndef TL_OPTIONAL_NO_CONSTRR\n template constexpr auto and_then(F &&f) const && {\n using result = detail::invoke_result_t;\n static_assert(detail::is_optional::value,\n \"F must return an optional\");\n\n return has_value() ? detail::invoke(std::forward(f), std::move(**this))\n : result(nullopt);\n }\n#endif\n#else\n /// Carries out some operation which returns an optional on the stored\n /// object if there is one.\n template \n TL_OPTIONAL_11_CONSTEXPR detail::invoke_result_t and_then(F &&f) & {\n using result = detail::invoke_result_t;\n static_assert(detail::is_optional::value,\n \"F must return an optional\");\n\n return has_value() ? detail::invoke(std::forward(f), **this)\n : result(nullopt);\n }\n\n template \n TL_OPTIONAL_11_CONSTEXPR detail::invoke_result_t and_then(F &&f) && {\n using result = detail::invoke_result_t;\n static_assert(detail::is_optional::value,\n \"F must return an optional\");\n\n return has_value() ? detail::invoke(std::forward(f), std::move(**this))\n : result(nullopt);\n }\n\n template \n constexpr detail::invoke_result_t and_then(F &&f) const & {\n using result = detail::invoke_result_t;\n static_assert(detail::is_optional::value,\n \"F must return an optional\");\n\n return has_value() ? detail::invoke(std::forward(f), **this)\n : result(nullopt);\n }\n\n#ifndef TL_OPTIONAL_NO_CONSTRR\n template \n constexpr detail::invoke_result_t and_then(F &&f) const && {\n using result = detail::invoke_result_t;\n static_assert(detail::is_optional::value,\n \"F must return an optional\");\n\n return has_value() ? detail::invoke(std::forward(f), std::move(**this))\n : result(nullopt);\n }\n#endif\n#endif\n\n#if defined(TL_OPTIONAL_CXX14) && !defined(TL_OPTIONAL_GCC49) && \\\n !defined(TL_OPTIONAL_GCC54) && !defined(TL_OPTIONAL_GCC55)\n /// Carries out some operation on the stored object if there is one.\n template TL_OPTIONAL_11_CONSTEXPR auto map(F &&f) & {\n return optional_map_impl(*this, std::forward(f));\n }\n\n template TL_OPTIONAL_11_CONSTEXPR auto map(F &&f) && {\n return optional_map_impl(std::move(*this), std::forward(f));\n }\n\n template constexpr auto map(F &&f) const & {\n return optional_map_impl(*this, std::forward(f));\n }\n\n template constexpr auto map(F &&f) const && {\n return optional_map_impl(std::move(*this), std::forward(f));\n }\n#else\n /// Carries out some operation on the stored object if there is one.\n template \n TL_OPTIONAL_11_CONSTEXPR decltype(optional_map_impl(std::declval(),\n std::declval()))\n map(F &&f) & {\n return optional_map_impl(*this, std::forward(f));\n }\n\n template \n TL_OPTIONAL_11_CONSTEXPR decltype(optional_map_impl(std::declval(),\n std::declval()))\n map(F &&f) && {\n return optional_map_impl(std::move(*this), std::forward(f));\n }\n\n template \n constexpr decltype(optional_map_impl(std::declval(),\n std::declval()))\n map(F &&f) const & {\n return optional_map_impl(*this, std::forward(f));\n }\n\n#ifndef TL_OPTIONAL_NO_CONSTRR\n template \n constexpr decltype(optional_map_impl(std::declval(),\n std::declval()))\n map(F &&f) const && {\n return optional_map_impl(std::move(*this), std::forward(f));\n }\n#endif\n#endif\n\n#if defined(TL_OPTIONAL_CXX14) && !defined(TL_OPTIONAL_GCC49) && \\\n !defined(TL_OPTIONAL_GCC54) && !defined(TL_OPTIONAL_GCC55)\n /// Carries out some operation on the stored object if there is one.\n template TL_OPTIONAL_11_CONSTEXPR auto transform(F&& f) & {\n return optional_map_impl(*this, std::forward(f));\n }\n\n template TL_OPTIONAL_11_CONSTEXPR auto transform(F&& f) && {\n return optional_map_impl(std::move(*this), std::forward(f));\n }\n\n template constexpr auto transform(F&& f) const & {\n return optional_map_impl(*this, std::forward(f));\n }\n\n template constexpr auto transform(F&& f) const && {\n return optional_map_impl(std::move(*this), std::forward(f));\n }\n#else\n /// Carries out some operation on the stored object if there is one.\n template \n TL_OPTIONAL_11_CONSTEXPR decltype(optional_map_impl(std::declval(),\n std::declval()))\n transform(F&& f) & {\n return optional_map_impl(*this, std::forward(f));\n }\n\n template \n TL_OPTIONAL_11_CONSTEXPR decltype(optional_map_impl(std::declval(),\n std::declval()))\n transform(F&& f) && {\n return optional_map_impl(std::move(*this), std::forward(f));\n }\n\n template \n constexpr decltype(optional_map_impl(std::declval(),\n std::declval()))\n transform(F&& f) const & {\n return optional_map_impl(*this, std::forward(f));\n }\n\n#ifndef TL_OPTIONAL_NO_CONSTRR\n template \n constexpr decltype(optional_map_impl(std::declval(),\n std::declval()))\n transform(F&& f) const && {\n return optional_map_impl(std::move(*this), std::forward(f));\n }\n#endif\n#endif\n\n /// Calls `f` if the optional is empty\n template * = nullptr>\n optional TL_OPTIONAL_11_CONSTEXPR or_else(F &&f) & {\n if (has_value())\n return *this;\n\n std::forward(f)();\n return nullopt;\n }\n\n template * = nullptr>\n optional TL_OPTIONAL_11_CONSTEXPR or_else(F &&f) & {\n return has_value() ? *this : std::forward(f)();\n }\n\n template * = nullptr>\n optional or_else(F &&f) && {\n if (has_value())\n return std::move(*this);\n\n std::forward(f)();\n return nullopt;\n }\n\n template * = nullptr>\n optional TL_OPTIONAL_11_CONSTEXPR or_else(F &&f) && {\n return has_value() ? std::move(*this) : std::forward(f)();\n }\n\n template * = nullptr>\n optional or_else(F &&f) const & {\n if (has_value())\n return *this;\n\n std::forward(f)();\n return nullopt;\n }\n\n template * = nullptr>\n optional TL_OPTIONAL_11_CONSTEXPR or_else(F &&f) const & {\n return has_value() ? *this : std::forward(f)();\n }\n\n#ifndef TL_OPTIONAL_NO_CONSTRR\n template * = nullptr>\n optional or_else(F &&f) const && {\n if (has_value())\n return std::move(*this);\n\n std::forward(f)();\n return nullopt;\n }\n\n template * = nullptr>\n optional or_else(F &&f) const && {\n return has_value() ? std::move(*this) : std::forward(f)();\n }\n#endif\n\n /// Maps the stored value with `f` if there is one, otherwise returns `u`.\n template U map_or(F &&f, U &&u) & {\n return has_value() ? detail::invoke(std::forward(f), **this)\n : std::forward(u);\n }\n\n template U map_or(F &&f, U &&u) && {\n return has_value() ? detail::invoke(std::forward(f), std::move(**this))\n : std::forward(u);\n }\n\n template U map_or(F &&f, U &&u) const & {\n return has_value() ? detail::invoke(std::forward(f), **this)\n : std::forward(u);\n }\n\n#ifndef TL_OPTIONAL_NO_CONSTRR\n template U map_or(F &&f, U &&u) const && {\n return has_value() ? detail::invoke(std::forward(f), std::move(**this))\n : std::forward(u);\n }\n#endif\n\n /// Maps the stored value with `f` if there is one, otherwise calls\n /// `u` and returns the result.\n template \n detail::invoke_result_t map_or_else(F &&f, U &&u) & {\n return has_value() ? detail::invoke(std::forward(f), **this)\n : std::forward(u)();\n }\n\n template \n detail::invoke_result_t map_or_else(F &&f, U &&u) && {\n return has_value() ? detail::invoke(std::forward(f), std::move(**this))\n : std::forward(u)();\n }\n\n template \n detail::invoke_result_t map_or_else(F &&f, U &&u) const & {\n return has_value() ? detail::invoke(std::forward(f), **this)\n : std::forward(u)();\n }\n\n#ifndef TL_OPTIONAL_NO_CONSTRR\n template \n detail::invoke_result_t map_or_else(F &&f, U &&u) const && {\n return has_value() ? detail::invoke(std::forward(f), std::move(**this))\n : std::forward(u)();\n }\n#endif\n\n /// Returns `u` if `*this` has a value, otherwise an empty optional.\n template \n constexpr optional::type> conjunction(U &&u) const {\n using result = optional>;\n return has_value() ? result{u} : result{nullopt};\n }\n\n /// Returns `rhs` if `*this` is empty, otherwise the current value.\n TL_OPTIONAL_11_CONSTEXPR optional disjunction(const optional &rhs) & {\n return has_value() ? *this : rhs;\n }\n\n constexpr optional disjunction(const optional &rhs) const & {\n return has_value() ? *this : rhs;\n }\n\n TL_OPTIONAL_11_CONSTEXPR optional disjunction(const optional &rhs) && {\n return has_value() ? std::move(*this) : rhs;\n }\n\n#ifndef TL_OPTIONAL_NO_CONSTRR\n constexpr optional disjunction(const optional &rhs) const && {\n return has_value() ? std::move(*this) : rhs;\n }\n#endif\n\n TL_OPTIONAL_11_CONSTEXPR optional disjunction(optional &&rhs) & {\n return has_value() ? *this : std::move(rhs);\n }\n\n constexpr optional disjunction(optional &&rhs) const & {\n return has_value() ? *this : std::move(rhs);\n }\n\n TL_OPTIONAL_11_CONSTEXPR optional disjunction(optional &&rhs) && {\n return has_value() ? std::move(*this) : std::move(rhs);\n }\n\n#ifndef TL_OPTIONAL_NO_CONSTRR\n constexpr optional disjunction(optional &&rhs) const && {\n return has_value() ? std::move(*this) : std::move(rhs);\n }\n#endif\n\n /// Takes the value out of the optional, leaving it empty\n optional take() {\n optional ret = std::move(*this);\n reset();\n return ret;\n }\n\n using value_type = T;\n\n /// Constructs an optional that does not contain a value.\n constexpr optional() noexcept = default;\n\n constexpr optional(nullopt_t) noexcept {}\n\n /// Copy constructor\n ///\n /// If `rhs` contains a value, the stored value is direct-initialized with\n /// it. Otherwise, the constructed optional is empty.\n TL_OPTIONAL_11_CONSTEXPR optional(const optional &rhs) = default;\n\n /// Move constructor\n ///\n /// If `rhs` contains a value, the stored value is direct-initialized with\n /// it. Otherwise, the constructed optional is empty.\n TL_OPTIONAL_11_CONSTEXPR optional(optional &&rhs) = default;\n\n /// Constructs the stored value in-place using the given arguments.\n template \n constexpr explicit optional(\n detail::enable_if_t::value, in_place_t>,\n Args &&... args)\n : base(in_place, std::forward(args)...) {}\n\n template \n TL_OPTIONAL_11_CONSTEXPR explicit optional(\n detail::enable_if_t &,\n Args &&...>::value,\n in_place_t>,\n std::initializer_list il, Args &&... args) {\n this->construct(il, std::forward(args)...);\n }\n\n /// Constructs the stored value with `u`.\n template <\n class U = T,\n detail::enable_if_t::value> * = nullptr,\n detail::enable_forward_value * = nullptr>\n constexpr optional(U &&u) : base(in_place, std::forward(u)) {}\n\n template <\n class U = T,\n detail::enable_if_t::value> * = nullptr,\n detail::enable_forward_value * = nullptr>\n constexpr explicit optional(U &&u) : base(in_place, std::forward(u)) {}\n\n /// Converting copy constructor.\n template <\n class U, detail::enable_from_other * = nullptr,\n detail::enable_if_t::value> * = nullptr>\n optional(const optional &rhs) {\n if (rhs.has_value()) {\n this->construct(*rhs);\n }\n }\n\n template * = nullptr,\n detail::enable_if_t::value> * =\n nullptr>\n explicit optional(const optional &rhs) {\n if (rhs.has_value()) {\n this->construct(*rhs);\n }\n }\n\n /// Converting move constructor.\n template <\n class U, detail::enable_from_other * = nullptr,\n detail::enable_if_t::value> * = nullptr>\n optional(optional &&rhs) {\n if (rhs.has_value()) {\n this->construct(std::move(*rhs));\n }\n }\n\n template <\n class U, detail::enable_from_other * = nullptr,\n detail::enable_if_t::value> * = nullptr>\n explicit optional(optional &&rhs) {\n if (rhs.has_value()) {\n this->construct(std::move(*rhs));\n }\n }\n\n /// Destroys the stored value if there is one.\n ~optional() = default;\n\n /// Assignment to empty.\n ///\n /// Destroys the current value if there is one.\n optional &operator=(nullopt_t) noexcept {\n if (has_value()) {\n this->m_value.~T();\n this->m_has_value = false;\n }\n\n return *this;\n }\n\n /// Copy assignment.\n ///\n /// Copies the value from `rhs` if there is one. Otherwise resets the stored\n /// value in `*this`.\n optional &operator=(const optional &rhs) = default;\n\n /// Move assignment.\n ///\n /// Moves the value from `rhs` if there is one. Otherwise resets the stored\n /// value in `*this`.\n optional &operator=(optional &&rhs) = default;\n\n /// Assigns the stored value from `u`, destroying the old value if there was\n /// one.\n template * = nullptr>\n optional &operator=(U &&u) {\n if (has_value()) {\n this->m_value = std::forward(u);\n } else {\n this->construct(std::forward(u));\n }\n\n return *this;\n }\n\n /// Converting copy assignment operator.\n ///\n /// Copies the value from `rhs` if there is one. Otherwise resets the stored\n /// value in `*this`.\n template * = nullptr>\n optional &operator=(const optional &rhs) {\n if (has_value()) {\n if (rhs.has_value()) {\n this->m_value = *rhs;\n } else {\n this->hard_reset();\n }\n }\n\n if (rhs.has_value()) {\n this->construct(*rhs);\n }\n\n return *this;\n }\n\n // TODO check exception guarantee\n /// Converting move assignment operator.\n ///\n /// Moves the value from `rhs` if there is one. Otherwise resets the stored\n /// value in `*this`.\n template * = nullptr>\n optional &operator=(optional &&rhs) {\n if (has_value()) {\n if (rhs.has_value()) {\n this->m_value = std::move(*rhs);\n } else {\n this->hard_reset();\n }\n }\n\n if (rhs.has_value()) {\n this->construct(std::move(*rhs));\n }\n\n return *this;\n }\n\n /// Constructs the value in-place, destroying the current one if there is\n /// one.\n template T &emplace(Args &&... args) {\n static_assert(std::is_constructible::value,\n \"T must be constructible with Args\");\n\n *this = nullopt;\n this->construct(std::forward(args)...);\n return value();\n }\n\n template \n detail::enable_if_t<\n std::is_constructible &, Args &&...>::value,\n T &>\n emplace(std::initializer_list il, Args &&... args) {\n *this = nullopt;\n this->construct(il, std::forward(args)...);\n return value(); \n }\n\n /// Swaps this optional with the other.\n ///\n /// If neither optionals have a value, nothing happens.\n /// If both have a value, the values are swapped.\n /// If one has a value, it is moved to the other and the movee is left\n /// valueless.\n void\n swap(optional &rhs) noexcept(std::is_nothrow_move_constructible::value\n &&detail::is_nothrow_swappable::value) {\n using std::swap;\n if (has_value()) {\n if (rhs.has_value()) {\n swap(**this, *rhs);\n } else {\n new (std::addressof(rhs.m_value)) T(std::move(this->m_value));\n this->m_value.T::~T();\n }\n } else if (rhs.has_value()) {\n new (std::addressof(this->m_value)) T(std::move(rhs.m_value));\n rhs.m_value.T::~T();\n }\n swap(this->m_has_value, rhs.m_has_value);\n }\n\n /// Returns a pointer to the stored value\n constexpr const T *operator->() const {\n return std::addressof(this->m_value);\n }\n\n TL_OPTIONAL_11_CONSTEXPR T *operator->() {\n return std::addressof(this->m_value);\n }\n\n /// Returns the stored value\n TL_OPTIONAL_11_CONSTEXPR T &operator*() & { return this->m_value; }\n\n constexpr const T &operator*() const & { return this->m_value; }\n\n TL_OPTIONAL_11_CONSTEXPR T &&operator*() && {\n return std::move(this->m_value);\n }\n\n#ifndef TL_OPTIONAL_NO_CONSTRR\n constexpr const T &&operator*() const && { return std::move(this->m_value); }\n#endif\n\n /// Returns whether or not the optional has a value\n constexpr bool has_value() const noexcept { return this->m_has_value; }\n\n constexpr explicit operator bool() const noexcept {\n return this->m_has_value;\n }\n\n /// Returns the contained value if there is one, otherwise throws bad_optional_access\n TL_OPTIONAL_11_CONSTEXPR T &value() & {\n if (has_value())\n return this->m_value;\n throw bad_optional_access();\n }\n TL_OPTIONAL_11_CONSTEXPR const T &value() const & {\n if (has_value())\n return this->m_value;\n throw bad_optional_access();\n }\n TL_OPTIONAL_11_CONSTEXPR T &&value() && {\n if (has_value())\n return std::move(this->m_value);\n throw bad_optional_access();\n }\n\n#ifndef TL_OPTIONAL_NO_CONSTRR\n TL_OPTIONAL_11_CONSTEXPR const T &&value() const && {\n if (has_value())\n return std::move(this->m_value);\n throw bad_optional_access();\n }\n#endif\n\n /// Returns the stored value if there is one, otherwise returns `u`\n template constexpr T value_or(U &&u) const & {\n static_assert(std::is_copy_constructible::value &&\n std::is_convertible::value,\n \"T must be copy constructible and convertible from U\");\n return has_value() ? **this : static_cast(std::forward(u));\n }\n\n template TL_OPTIONAL_11_CONSTEXPR T value_or(U &&u) && {\n static_assert(std::is_move_constructible::value &&\n std::is_convertible::value,\n \"T must be move constructible and convertible from U\");\n return has_value() ? **this : static_cast(std::forward(u));\n }\n\n /// Destroys the stored value if one exists, making the optional empty\n void reset() noexcept {\n if (has_value()) {\n this->m_value.~T();\n this->m_has_value = false;\n }\n }\n}; // namespace tl\n\n/// Compares two optional objects\ntemplate \ninline constexpr bool operator==(const optional &lhs,\n const optional &rhs) {\n return lhs.has_value() == rhs.has_value() &&\n (!lhs.has_value() || *lhs == *rhs);\n}\ntemplate \ninline constexpr bool operator!=(const optional &lhs,\n const optional &rhs) {\n return lhs.has_value() != rhs.has_value() ||\n (lhs.has_value() && *lhs != *rhs);\n}\ntemplate \ninline constexpr bool operator<(const optional &lhs,\n const optional &rhs) {\n return rhs.has_value() && (!lhs.has_value() || *lhs < *rhs);\n}\ntemplate \ninline constexpr bool operator>(const optional &lhs,\n const optional &rhs) {\n return lhs.has_value() && (!rhs.has_value() || *lhs > *rhs);\n}\ntemplate \ninline constexpr bool operator<=(const optional &lhs,\n const optional &rhs) {\n return !lhs.has_value() || (rhs.has_value() && *lhs <= *rhs);\n}\ntemplate \ninline constexpr bool operator>=(const optional &lhs,\n const optional &rhs) {\n return !rhs.has_value() || (lhs.has_value() && *lhs >= *rhs);\n}\n\n/// Compares an optional to a `nullopt`\ntemplate \ninline constexpr bool operator==(const optional &lhs, nullopt_t) noexcept {\n return !lhs.has_value();\n}\ntemplate \ninline constexpr bool operator==(nullopt_t, const optional &rhs) noexcept {\n return !rhs.has_value();\n}\ntemplate \ninline constexpr bool operator!=(const optional &lhs, nullopt_t) noexcept {\n return lhs.has_value();\n}\ntemplate \ninline constexpr bool operator!=(nullopt_t, const optional &rhs) noexcept {\n return rhs.has_value();\n}\ntemplate \ninline constexpr bool operator<(const optional &, nullopt_t) noexcept {\n return false;\n}\ntemplate \ninline constexpr bool operator<(nullopt_t, const optional &rhs) noexcept {\n return rhs.has_value();\n}\ntemplate \ninline constexpr bool operator<=(const optional &lhs, nullopt_t) noexcept {\n return !lhs.has_value();\n}\ntemplate \ninline constexpr bool operator<=(nullopt_t, const optional &) noexcept {\n return true;\n}\ntemplate \ninline constexpr bool operator>(const optional &lhs, nullopt_t) noexcept {\n return lhs.has_value();\n}\ntemplate \ninline constexpr bool operator>(nullopt_t, const optional &) noexcept {\n return false;\n}\ntemplate \ninline constexpr bool operator>=(const optional &, nullopt_t) noexcept {\n return true;\n}\ntemplate \ninline constexpr bool operator>=(nullopt_t, const optional &rhs) noexcept {\n return !rhs.has_value();\n}\n\n/// Compares the optional with a value.\ntemplate \ninline constexpr bool operator==(const optional &lhs, const U &rhs) {\n return lhs.has_value() ? *lhs == rhs : false;\n}\ntemplate \ninline constexpr bool operator==(const U &lhs, const optional &rhs) {\n return rhs.has_value() ? lhs == *rhs : false;\n}\ntemplate \ninline constexpr bool operator!=(const optional &lhs, const U &rhs) {\n return lhs.has_value() ? *lhs != rhs : true;\n}\ntemplate \ninline constexpr bool operator!=(const U &lhs, const optional &rhs) {\n return rhs.has_value() ? lhs != *rhs : true;\n}\ntemplate \ninline constexpr bool operator<(const optional &lhs, const U &rhs) {\n return lhs.has_value() ? *lhs < rhs : true;\n}\ntemplate \ninline constexpr bool operator<(const U &lhs, const optional &rhs) {\n return rhs.has_value() ? lhs < *rhs : false;\n}\ntemplate \ninline constexpr bool operator<=(const optional &lhs, const U &rhs) {\n return lhs.has_value() ? *lhs <= rhs : true;\n}\ntemplate \ninline constexpr bool operator<=(const U &lhs, const optional &rhs) {\n return rhs.has_value() ? lhs <= *rhs : false;\n}\ntemplate \ninline constexpr bool operator>(const optional &lhs, const U &rhs) {\n return lhs.has_value() ? *lhs > rhs : false;\n}\ntemplate \ninline constexpr bool operator>(const U &lhs, const optional &rhs) {\n return rhs.has_value() ? lhs > *rhs : true;\n}\ntemplate \ninline constexpr bool operator>=(const optional &lhs, const U &rhs) {\n return lhs.has_value() ? *lhs >= rhs : false;\n}\ntemplate \ninline constexpr bool operator>=(const U &lhs, const optional &rhs) {\n return rhs.has_value() ? lhs >= *rhs : true;\n}\n\ntemplate ::value> * = nullptr,\n detail::enable_if_t::value> * = nullptr>\nvoid swap(optional &lhs,\n optional &rhs) noexcept(noexcept(lhs.swap(rhs))) {\n return lhs.swap(rhs);\n}\n\nnamespace detail {\nstruct i_am_secret {};\n} // namespace detail\n\ntemplate ::value,\n detail::decay_t, T>>\ninline constexpr optional make_optional(U &&v) {\n return optional(std::forward(v));\n}\n\ntemplate \ninline constexpr optional make_optional(Args &&... args) {\n return optional(in_place, std::forward(args)...);\n}\ntemplate \ninline constexpr optional make_optional(std::initializer_list il,\n Args &&... args) {\n return optional(in_place, il, std::forward(args)...);\n}\n\n#if __cplusplus >= 201703L\ntemplate optional(T)->optional;\n#endif\n\n/// \\exclude\nnamespace detail {\n#ifdef TL_OPTIONAL_CXX14\ntemplate (),\n *std::declval())),\n detail::enable_if_t::value> * = nullptr>\nconstexpr auto optional_map_impl(Opt &&opt, F &&f) {\n return opt.has_value()\n ? detail::invoke(std::forward(f), *std::forward(opt))\n : optional(nullopt);\n}\n\ntemplate (),\n *std::declval())),\n detail::enable_if_t::value> * = nullptr>\nauto optional_map_impl(Opt &&opt, F &&f) {\n if (opt.has_value()) {\n detail::invoke(std::forward(f), *std::forward(opt));\n return make_optional(monostate{});\n }\n\n return optional(nullopt);\n}\n#else\ntemplate (),\n *std::declval())),\n detail::enable_if_t::value> * = nullptr>\n\nconstexpr auto optional_map_impl(Opt &&opt, F &&f) -> optional {\n return opt.has_value()\n ? detail::invoke(std::forward(f), *std::forward(opt))\n : optional(nullopt);\n}\n\ntemplate (),\n *std::declval())),\n detail::enable_if_t::value> * = nullptr>\n\nauto optional_map_impl(Opt &&opt, F &&f) -> optional {\n if (opt.has_value()) {\n detail::invoke(std::forward(f), *std::forward(opt));\n return monostate{};\n }\n\n return nullopt;\n}\n#endif\n} // namespace detail\n\n/// Specialization for when `T` is a reference. `optional` acts similarly\n/// to a `T*`, but provides more operations and shows intent more clearly.\ntemplate class optional {\npublic:\n// The different versions for C++14 and 11 are needed because deduced return\n// types are not SFINAE-safe. This provides better support for things like\n// generic lambdas. C.f.\n// http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2017/p0826r0.html\n#if defined(TL_OPTIONAL_CXX14) && !defined(TL_OPTIONAL_GCC49) && \\\n !defined(TL_OPTIONAL_GCC54) && !defined(TL_OPTIONAL_GCC55)\n\n /// Carries out some operation which returns an optional on the stored\n /// object if there is one.\n template TL_OPTIONAL_11_CONSTEXPR auto and_then(F &&f) & {\n using result = detail::invoke_result_t;\n static_assert(detail::is_optional::value,\n \"F must return an optional\");\n\n return has_value() ? detail::invoke(std::forward(f), **this)\n : result(nullopt);\n }\n\n template TL_OPTIONAL_11_CONSTEXPR auto and_then(F &&f) && {\n using result = detail::invoke_result_t;\n static_assert(detail::is_optional::value,\n \"F must return an optional\");\n\n return has_value() ? detail::invoke(std::forward(f), **this)\n : result(nullopt);\n }\n\n template constexpr auto and_then(F &&f) const & {\n using result = detail::invoke_result_t;\n static_assert(detail::is_optional::value,\n \"F must return an optional\");\n\n return has_value() ? detail::invoke(std::forward(f), **this)\n : result(nullopt);\n }\n\n#ifndef TL_OPTIONAL_NO_CONSTRR\n template constexpr auto and_then(F &&f) const && {\n using result = detail::invoke_result_t;\n static_assert(detail::is_optional::value,\n \"F must return an optional\");\n\n return has_value() ? detail::invoke(std::forward(f), **this)\n : result(nullopt);\n }\n#endif\n#else\n /// Carries out some operation which returns an optional on the stored\n /// object if there is one.\n template \n TL_OPTIONAL_11_CONSTEXPR detail::invoke_result_t and_then(F &&f) & {\n using result = detail::invoke_result_t;\n static_assert(detail::is_optional::value,\n \"F must return an optional\");\n\n return has_value() ? detail::invoke(std::forward(f), **this)\n : result(nullopt);\n }\n\n template \n TL_OPTIONAL_11_CONSTEXPR detail::invoke_result_t and_then(F &&f) && {\n using result = detail::invoke_result_t;\n static_assert(detail::is_optional::value,\n \"F must return an optional\");\n\n return has_value() ? detail::invoke(std::forward(f), **this)\n : result(nullopt);\n }\n\n template \n constexpr detail::invoke_result_t and_then(F &&f) const & {\n using result = detail::invoke_result_t;\n static_assert(detail::is_optional::value,\n \"F must return an optional\");\n\n return has_value() ? detail::invoke(std::forward(f), **this)\n : result(nullopt);\n }\n\n#ifndef TL_OPTIONAL_NO_CONSTRR\n template \n constexpr detail::invoke_result_t and_then(F &&f) const && {\n using result = detail::invoke_result_t;\n static_assert(detail::is_optional::value,\n \"F must return an optional\");\n\n return has_value() ? detail::invoke(std::forward(f), **this)\n : result(nullopt);\n }\n#endif\n#endif\n\n#if defined(TL_OPTIONAL_CXX14) && !defined(TL_OPTIONAL_GCC49) && \\\n !defined(TL_OPTIONAL_GCC54) && !defined(TL_OPTIONAL_GCC55)\n /// Carries out some operation on the stored object if there is one.\n template TL_OPTIONAL_11_CONSTEXPR auto map(F &&f) & {\n return detail::optional_map_impl(*this, std::forward(f));\n }\n\n template TL_OPTIONAL_11_CONSTEXPR auto map(F &&f) && {\n return detail::optional_map_impl(std::move(*this), std::forward(f));\n }\n\n template constexpr auto map(F &&f) const & {\n return detail::optional_map_impl(*this, std::forward(f));\n }\n\n template constexpr auto map(F &&f) const && {\n return detail::optional_map_impl(std::move(*this), std::forward(f));\n }\n#else\n /// Carries out some operation on the stored object if there is one.\n template \n TL_OPTIONAL_11_CONSTEXPR decltype(detail::optional_map_impl(std::declval(),\n std::declval()))\n map(F &&f) & {\n return detail::optional_map_impl(*this, std::forward(f));\n }\n\n template \n TL_OPTIONAL_11_CONSTEXPR decltype(detail::optional_map_impl(std::declval(),\n std::declval()))\n map(F &&f) && {\n return detail::optional_map_impl(std::move(*this), std::forward(f));\n }\n\n template \n constexpr decltype(detail::optional_map_impl(std::declval(),\n std::declval()))\n map(F &&f) const & {\n return detail::optional_map_impl(*this, std::forward(f));\n }\n\n#ifndef TL_OPTIONAL_NO_CONSTRR\n template \n constexpr decltype(detail::optional_map_impl(std::declval(),\n std::declval()))\n map(F &&f) const && {\n return detail::optional_map_impl(std::move(*this), std::forward(f));\n }\n#endif\n#endif\n\n#if defined(TL_OPTIONAL_CXX14) && !defined(TL_OPTIONAL_GCC49) && \\\n !defined(TL_OPTIONAL_GCC54) && !defined(TL_OPTIONAL_GCC55)\n /// Carries out some operation on the stored object if there is one.\n template TL_OPTIONAL_11_CONSTEXPR auto transform(F&& f) & {\n return detail::optional_map_impl(*this, std::forward(f));\n }\n\n template TL_OPTIONAL_11_CONSTEXPR auto transform(F&& f) && {\n return detail::optional_map_impl(std::move(*this), std::forward(f));\n }\n\n template constexpr auto transform(F&& f) const & {\n return detail::optional_map_impl(*this, std::forward(f));\n }\n\n template constexpr auto transform(F&& f) const && {\n return detail::optional_map_impl(std::move(*this), std::forward(f));\n }\n#else\n /// Carries out some operation on the stored object if there is one.\n template \n TL_OPTIONAL_11_CONSTEXPR decltype(detail::optional_map_impl(std::declval(),\n std::declval()))\n transform(F&& f) & {\n return detail::optional_map_impl(*this, std::forward(f));\n }\n\n /// \\group map\n /// \\synopsis template auto transform(F &&f) &&;\n template \n TL_OPTIONAL_11_CONSTEXPR decltype(detail::optional_map_impl(std::declval(),\n std::declval()))\n transform(F&& f) && {\n return detail::optional_map_impl(std::move(*this), std::forward(f));\n }\n\n template \n constexpr decltype(detail::optional_map_impl(std::declval(),\n std::declval()))\n transform(F&& f) const & {\n return detail::optional_map_impl(*this, std::forward(f));\n }\n\n#ifndef TL_OPTIONAL_NO_CONSTRR\n template \n constexpr decltype(detail::optional_map_impl(std::declval(),\n std::declval()))\n transform(F&& f) const && {\n return detail::optional_map_impl(std::move(*this), std::forward(f));\n }\n#endif\n#endif\n\n /// Calls `f` if the optional is empty\n template * = nullptr>\n optional TL_OPTIONAL_11_CONSTEXPR or_else(F &&f) & {\n if (has_value())\n return *this;\n\n std::forward(f)();\n return nullopt;\n }\n\n template * = nullptr>\n optional TL_OPTIONAL_11_CONSTEXPR or_else(F &&f) & {\n return has_value() ? *this : std::forward(f)();\n }\n\n template * = nullptr>\n optional or_else(F &&f) && {\n if (has_value())\n return std::move(*this);\n\n std::forward(f)();\n return nullopt;\n }\n\n template * = nullptr>\n optional TL_OPTIONAL_11_CONSTEXPR or_else(F &&f) && {\n return has_value() ? std::move(*this) : std::forward(f)();\n }\n\n template * = nullptr>\n optional or_else(F &&f) const & {\n if (has_value())\n return *this;\n\n std::forward(f)();\n return nullopt;\n }\n\n template * = nullptr>\n optional TL_OPTIONAL_11_CONSTEXPR or_else(F &&f) const & {\n return has_value() ? *this : std::forward(f)();\n }\n\n#ifndef TL_OPTIONAL_NO_CONSTRR\n template * = nullptr>\n optional or_else(F &&f) const && {\n if (has_value())\n return std::move(*this);\n\n std::forward(f)();\n return nullopt;\n }\n\n template * = nullptr>\n optional or_else(F &&f) const && {\n return has_value() ? std::move(*this) : std::forward(f)();\n }\n#endif\n\n /// Maps the stored value with `f` if there is one, otherwise returns `u`\n template U map_or(F &&f, U &&u) & {\n return has_value() ? detail::invoke(std::forward(f), **this)\n : std::forward(u);\n }\n\n template U map_or(F &&f, U &&u) && {\n return has_value() ? detail::invoke(std::forward(f), std::move(**this))\n : std::forward(u);\n }\n\n template U map_or(F &&f, U &&u) const & {\n return has_value() ? detail::invoke(std::forward(f), **this)\n : std::forward(u);\n }\n\n#ifndef TL_OPTIONAL_NO_CONSTRR\n template U map_or(F &&f, U &&u) const && {\n return has_value() ? detail::invoke(std::forward(f), std::move(**this))\n : std::forward(u);\n }\n#endif\n\n /// Maps the stored value with `f` if there is one, otherwise calls\n /// `u` and returns the result.\n template \n detail::invoke_result_t map_or_else(F &&f, U &&u) & {\n return has_value() ? detail::invoke(std::forward(f), **this)\n : std::forward(u)();\n }\n\n template \n detail::invoke_result_t map_or_else(F &&f, U &&u) && {\n return has_value() ? detail::invoke(std::forward(f), std::move(**this))\n : std::forward(u)();\n }\n\n template \n detail::invoke_result_t map_or_else(F &&f, U &&u) const & {\n return has_value() ? detail::invoke(std::forward(f), **this)\n : std::forward(u)();\n }\n\n#ifndef TL_OPTIONAL_NO_CONSTRR\n template \n detail::invoke_result_t map_or_else(F &&f, U &&u) const && {\n return has_value() ? detail::invoke(std::forward(f), std::move(**this))\n : std::forward(u)();\n }\n#endif\n\n /// Returns `u` if `*this` has a value, otherwise an empty optional.\n template \n constexpr optional::type> conjunction(U &&u) const {\n using result = optional>;\n return has_value() ? result{u} : result{nullopt};\n }\n\n /// Returns `rhs` if `*this` is empty, otherwise the current value.\n TL_OPTIONAL_11_CONSTEXPR optional disjunction(const optional &rhs) & {\n return has_value() ? *this : rhs;\n }\n\n constexpr optional disjunction(const optional &rhs) const & {\n return has_value() ? *this : rhs;\n }\n\n TL_OPTIONAL_11_CONSTEXPR optional disjunction(const optional &rhs) && {\n return has_value() ? std::move(*this) : rhs;\n }\n\n#ifndef TL_OPTIONAL_NO_CONSTRR\n constexpr optional disjunction(const optional &rhs) const && {\n return has_value() ? std::move(*this) : rhs;\n }\n#endif\n\n TL_OPTIONAL_11_CONSTEXPR optional disjunction(optional &&rhs) & {\n return has_value() ? *this : std::move(rhs);\n }\n\n constexpr optional disjunction(optional &&rhs) const & {\n return has_value() ? *this : std::move(rhs);\n }\n\n TL_OPTIONAL_11_CONSTEXPR optional disjunction(optional &&rhs) && {\n return has_value() ? std::move(*this) : std::move(rhs);\n }\n\n#ifndef TL_OPTIONAL_NO_CONSTRR\n constexpr optional disjunction(optional &&rhs) const && {\n return has_value() ? std::move(*this) : std::move(rhs);\n }\n#endif\n\n /// Takes the value out of the optional, leaving it empty\n optional take() {\n optional ret = std::move(*this);\n reset();\n return ret;\n }\n\n using value_type = T &;\n\n /// Constructs an optional that does not contain a value.\n constexpr optional() noexcept : m_value(nullptr) {}\n\n constexpr optional(nullopt_t) noexcept : m_value(nullptr) {}\n\n /// Copy constructor\n ///\n /// If `rhs` contains a value, the stored value is direct-initialized with\n /// it. Otherwise, the constructed optional is empty.\n TL_OPTIONAL_11_CONSTEXPR optional(const optional &rhs) noexcept = default;\n\n /// Move constructor\n ///\n /// If `rhs` contains a value, the stored value is direct-initialized with\n /// it. Otherwise, the constructed optional is empty.\n TL_OPTIONAL_11_CONSTEXPR optional(optional &&rhs) = default;\n\n /// Constructs the stored value with `u`.\n template >::value>\n * = nullptr>\n constexpr optional(U &&u) noexcept : m_value(std::addressof(u)) {\n static_assert(std::is_lvalue_reference::value, \"U must be an lvalue\");\n }\n\n template \n constexpr explicit optional(const optional &rhs) noexcept : optional(*rhs) {}\n\n /// No-op\n ~optional() = default;\n\n /// Assignment to empty.\n ///\n /// Destroys the current value if there is one.\n optional &operator=(nullopt_t) noexcept {\n m_value = nullptr;\n return *this;\n }\n\n /// Copy assignment.\n ///\n /// Rebinds this optional to the referee of `rhs` if there is one. Otherwise\n /// resets the stored value in `*this`.\n optional &operator=(const optional &rhs) = default;\n\n /// Rebinds this optional to `u`.\n template >::value>\n * = nullptr>\n optional &operator=(U &&u) {\n static_assert(std::is_lvalue_reference::value, \"U must be an lvalue\");\n m_value = std::addressof(u);\n return *this;\n }\n\n /// Converting copy assignment operator.\n ///\n /// Rebinds this optional to the referee of `rhs` if there is one. Otherwise\n /// resets the stored value in `*this`.\n template optional &operator=(const optional &rhs) noexcept {\n m_value = std::addressof(rhs.value());\n return *this;\n }\n\n /// Rebinds this optional to `u`.\n template >::value>\n * = nullptr>\n optional &emplace(U &&u) noexcept {\n return *this = std::forward(u);\n }\n\n void swap(optional &rhs) noexcept { std::swap(m_value, rhs.m_value); }\n\n /// Returns a pointer to the stored value\n constexpr const T *operator->() const noexcept { return m_value; }\n\n TL_OPTIONAL_11_CONSTEXPR T *operator->() noexcept { return m_value; }\n\n /// Returns the stored value\n TL_OPTIONAL_11_CONSTEXPR T &operator*() noexcept { return *m_value; }\n\n constexpr const T &operator*() const noexcept { return *m_value; }\n\n constexpr bool has_value() const noexcept { return m_value != nullptr; }\n\n constexpr explicit operator bool() const noexcept {\n return m_value != nullptr;\n }\n\n /// Returns the contained value if there is one, otherwise throws bad_optional_access\n TL_OPTIONAL_11_CONSTEXPR T &value() {\n if (has_value())\n return *m_value;\n throw bad_optional_access();\n }\n TL_OPTIONAL_11_CONSTEXPR const T &value() const {\n if (has_value())\n return *m_value;\n throw bad_optional_access();\n }\n\n /// Returns the stored value if there is one, otherwise returns `u`\n template constexpr T value_or(U &&u) const & noexcept {\n static_assert(std::is_copy_constructible::value &&\n std::is_convertible::value,\n \"T must be copy constructible and convertible from U\");\n return has_value() ? **this : static_cast(std::forward(u));\n }\n\n /// \\group value_or\n template TL_OPTIONAL_11_CONSTEXPR T value_or(U &&u) && noexcept {\n static_assert(std::is_move_constructible::value &&\n std::is_convertible::value,\n \"T must be move constructible and convertible from U\");\n return has_value() ? **this : static_cast(std::forward(u));\n }\n\n /// Destroys the stored value if one exists, making the optional empty\n void reset() noexcept { m_value = nullptr; }\n\nprivate:\n T *m_value;\n}; // namespace tl\n\n\n\n} // namespace tl\n\nnamespace std {\n// TODO SFINAE\ntemplate struct hash> {\n ::std::size_t operator()(const tl::optional &o) const {\n if (!o.has_value())\n return 0;\n\n return std::hash>()(*o);\n }\n};\n} // namespace std\n\n#endif\n" }, { "path": "Externals/partio/CMakeLists.txt", "content": "# PARTIO SOFTWARE\n# Copyright 2010 Disney Enterprises, Inc. All rights reserved\n# \n# Redistribution and use in source and binary forms, with or without\n# modification, are permitted provided that the following conditions are\n# met:\n# \n# * Redistributions of source code must retain the above copyright\n# notice, this list of conditions and the following disclaimer.\n# \n# * Redistributions in binary form must reproduce the above copyright\n# notice, this list of conditions and the following disclaimer in\n# the documentation and/or other materials provided with the\n# distribution.\n# \n# * The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\n# Studios\" or the names of its contributors may NOT be used to\n# endorse or promote products derived from this software without\n# specific prior written permission from Walt Disney Pictures.\n# \n# Disclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\n# CONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\n# BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\n# FOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\n# IN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\n# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\n# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\n# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\n# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\n# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\n# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n\nCMAKE_MINIMUM_REQUIRED( VERSION 3.8.0 )\nSET( CMAKE_SKIP_RPATH TRUE )\n\n## project name & version\nPROJECT(partio LANGUAGES CXX VERSION 1.5.2)\n\n# Enable C++11\nSET(CMAKE_CXX_STANDARD 11)\nSET(CMAKE_CXX_STANDARD_REQUIRED YES)\nSET(CMAKE_CXX_EXTENSIONS NO)\n\n## Setup platform specific helper defines build variants\nIF(WIN32)\n IF(MSVC)\n ADD_DEFINITIONS (-DPARTIO_WIN32)\n ENDIF()\n ADD_DEFINITIONS (-D_USE_MATH_DEFINES)\nELSE()\n ADD_COMPILE_OPTIONS (-Wextra -Wno-unused-parameter)\nENDIF()\nIF(APPLE)\n set (CMAKE_SHARED_LINKER_FLAGS \"-undefined dynamic_lookup\")\nENDIF()\n\nSET(CMAKE_BUILD_TYPE \"Release\" CACHE STRING \"type of build\" FORCE)\n\n## Set install location\nIF(CMAKE_INSTALL_PREFIX_INITIALIZED_TO_DEFAULT)\n IF(WIN32)\n set(VARIANT_DIRECTORY \"Windows-x86_64\")\n ELSE()\n execute_process(COMMAND sh -c \"echo `uname`-`uname -r | cut -d'-' -f1`-`uname -m`\" OUTPUT_VARIABLE VARIANT_DIRECTORY OUTPUT_STRIP_TRAILING_WHITESPACE)\n ENDIF()\n set(CMAKE_INSTALL_PREFIX \"${CMAKE_SOURCE_DIR}/${VARIANT_DIRECTORY}\")\nENDIF(CMAKE_INSTALL_PREFIX_INITIALIZED_TO_DEFAULT)\n\nSET (ZLIB_LIBRARY \"\")\n\n#option(BUILD_SHARED_LIBS \"Enabled shared libraries\" OFF)\n\n\nfile(GLOB io_cpp \"io/*.cpp\")\nfile(GLOB core_cpp \"core/*.cpp\")\n\nadd_library(partio ${io_cpp} ${core_cpp})\nset_target_properties(partio PROPERTIES OUTPUT_NAME partio POSITION_INDEPENDENT_CODE ON)\nif (WIN32)\nif (MSVC)\n #target_compile_options(partio PUBLIC /MT)\n target_link_options(partio PRIVATE /INCREMENTAL:NO /NODEFAULTLIB:MSVCRT)\nendif()\nendif()\n\ntarget_include_directories(partio\n\tSYSTEM\n PUBLIC\n $)\n" }, { "path": "Externals/partio/Partio.h", "content": "/*\nPARTIO SOFTWARE\nCopyright 2010 Disney Enterprises, Inc. All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n*/\n\n/*!\n The interface of the particle API (Partio)\n what type the primitive is, how many instances of the primitive there, name of\n the attribute and an index which speeds lookups of data\n*/\n#ifndef _Partioh_\n#define _Partioh_\n\n#include \n#include \n#include \n#include \n#include \n#include \"PartioAttribute.h\"\n#include \"PartioIterator.h\"\n\nnamespace Partio{\n\n//! Opaque random access method to a single particle. No number is implied or guaranteed.\ntypedef uint64_t ParticleIndex;\n\nclass ParticlesData;\nclass ParticlesDataMutable;\n// Particle Collection Interface\n//! Particle Collection Interface\n/*!\n This class provides ways of accessing basic information about particles,\n the number in the set, the attribute names and types, etc. No actual\n data can be read or written.\n*/\nclass ParticlesInfo\n{\nprotected:\n virtual ~ParticlesInfo() {}\npublic:\n\n //! Frees the memory if this particle set was created with create() or release()\n //! Reduces reference count if it was obtained with readCached()\n //! and if the ref count hits zero, frees the memory\n virtual void release()=0;\n\n //! Number of particles in the structure.\n virtual int numParticles() const=0;\n\n //! Number of per-particle attributes.\n virtual int numAttributes() const=0;\n //! Number of fixed attributes.\n virtual int numFixedAttributes() const=0;\n\n //! Lookup an attribute by name and store a handle to the attribute.\n virtual bool attributeInfo(const char* attributeName,ParticleAttribute& attribute) const=0;\n //! Lookup an attribute by name and store a handle to the attribute.\n virtual bool fixedAttributeInfo(const char* attributeName,FixedAttribute& attribute) const=0;\n\n //! Lookup an attribute by index and store a handle to the attribute.\n virtual bool attributeInfo(const int index,ParticleAttribute& attribute) const=0;\n //! Lookup an attribute by index and store a handle to the attribute.\n virtual bool fixedAttributeInfo(const int index,FixedAttribute& attribute) const=0;\n};\n\n// Particle Data Interface\n//! Particle Data Interface\n/*!\n This interface provides the ability to read data attributes for given particles\n and search for nearest neighbors using KD-Trees.\n*/\nclass ParticlesData:public ParticlesInfo\n{\nprotected:\n virtual ~ParticlesData() {}\npublic:\n friend void freeCached(ParticlesData* particles);\n\n typedef ParticleIterator const_iterator;\n\n //! Fill the user supplied values array with data corresponding to the given\n //! list of particles. Specify whether or not your indices are sorted.\n //! note if T is void, then type checking is disabled.\n template inline void data(const ParticleAttribute& attribute,\n const int indexCount,const ParticleIndex* particleIndices,const bool sorted,T* values)\n {\n \tassert(typeCheck(attribute.type));\n dataInternalMultiple(attribute,indexCount,particleIndices,sorted,(char*)values);\n }\n\n template inline const T* data(const ParticleAttribute& attribute,\n const ParticleIndex particleIndex) const\n {\n // TODO: add type checking\n return static_cast(dataInternal(attribute,particleIndex));\n }\n\n template inline const T* fixedData(const FixedAttribute& attribute) const\n {\n // TODO: add type checking\n return static_cast(fixedDataInternal(attribute));\n }\n\n /// All indexed strings for an attribute\n virtual const std::vector& indexedStrs(const ParticleAttribute& attr) const=0;\n /// All indexed strings for an attribute\n virtual const std::vector& fixedIndexedStrs(const FixedAttribute& attr) const=0;\n\n /// Looks up the index for a given string for a given attribute, returns -1 if not found\n virtual int lookupIndexedStr(const ParticleAttribute& attribute,const char* str) const=0;\n /// Looks up the index for a given string for a given attribute, returns -1 if not found\n virtual int lookupFixedIndexedStr(const FixedAttribute& attribute,const char* str) const=0;\n\n //! Fill the user supplied values array with data corresponding to the given\n //! list of particles. Specify whether or not your indices are sorted. Attributes\n //! that are not floating types are automatically casted before being placed\n //! in values.\n virtual void dataAsFloat(const ParticleAttribute& attribute,const int indexCount,\n const ParticleIndex* particleIndices,const bool sorted,float* values) const=0;\n\n //! Find the points within the bounding box specified.\n //! Must call sort() before using this function\n //! NOTE: points array is not pre-cleared.\n virtual void findPoints(const float bboxMin[3],const float bboxMax[3],\n std::vector& points) const=0;\n\n //! Find the N nearest neighbors that are within maxRadius distance using STL types\n //! (measured in standard 2-norm). If less than N are found within the\n //! radius, the search radius is not increased.\n //! NOTE: points/pointsDistancesSquared are cleared before use.\n //! Must call sort() before using this function\n virtual float findNPoints(const float center[3],int nPoints,const float maxRadius,\n std::vector& points,std::vector& pointDistancesSquared) const=0;\n\n //! Find the N nearest neighbors that are within maxRadius distance using POD types\n //! NOTE: returns the number of found points and leaves in finalRadius2 the\n //! square of the final search radius used\n virtual int findNPoints(const float center[3],int nPoints,const float maxRadius,\n ParticleIndex *points, float *pointDistancesSquared, float *finalRadius2) const=0;\n\n //! Produce a const iterator\n virtual const_iterator setupConstIterator(const int index=0) const=0;\n\n //! Produce a beginning iterator for the particles\n const_iterator begin() const\n {return setupConstIterator();}\n\n //! Produce a ending iterator for the particles\n const_iterator end() const\n {return const_iterator();}\n\nprivate:\n virtual void* dataInternal(const ParticleAttribute& attribute,const ParticleIndex particleIndex) const=0;\n virtual void* fixedDataInternal(const FixedAttribute& attribute) const=0;\n virtual void dataInternalMultiple(const ParticleAttribute& attribute,const int indexCount,\n const ParticleIndex* particleIndices,const bool sorted,char* values) const=0;\n};\n\n// Particle Mutable Data Interface\n//! Particle Mutable Data Interface\n/*!\n This interface provides the ability to write data attributes, add attributes,\n add particles, etc.\n*/\nclass ParticlesDataMutable:public ParticlesData\n{\nprotected:\n virtual ~ParticlesDataMutable(){}\n\npublic:\n\n typedef ParticleIterator iterator;\n\n //! Get a pointer to the data corresponding to the given particleIndex and\n //! attribute given by the attribute handle.\n template inline T* dataWrite(const ParticleAttribute& attribute,\n const ParticleIndex particleIndex) const\n {\n // TODO: add type checking\n return static_cast(dataInternal(attribute,particleIndex));\n }\n\n //! Get a pointer to the data corresponding to the attribute given by the\n //! fixed attribute handle.\n template inline T* fixedDataWrite(const FixedAttribute& attribute) const\n {\n // TODO: add type checking\n return static_cast(fixedDataInternal(attribute));\n }\n\n /// Set particle value for attribute\n template inline void set(const ParticleAttribute& attribute,\n const ParticleIndex particleIndex, const T* data) {\n T* ptr = static_cast(dataInternal(attribute, particleIndex));\n memcpy(ptr, data, attribute.count * TypeSize(attribute.type));\n }\n\n template inline void setFixed(const FixedAttribute& attribute, const T* data) {\n T* ptr = static_cast(fixedDataInternal(attribute));\n memcpy(ptr, data, attribute.count * TypeSize(attribute.type));\n }\n\n /// Returns a token for the given string. This allows efficient storage of string data\n virtual int registerIndexedStr(const ParticleAttribute& attribute,const char* str)=0;\n /// Returns a token for the given string. This allows efficient storage of string data\n virtual int registerFixedIndexedStr(const FixedAttribute& attribute,const char* str)=0;\n\n /// Returns a token for the given string. This allows efficient storage of string data\n virtual void setIndexedStr(const ParticleAttribute& attribute,int indexedStringToken,const char* str)=0;\n /// Returns a token for the given string. This allows efficient storage of string data\n virtual void setFixedIndexedStr(const FixedAttribute& attribute,int indexedStringToken,const char* str)=0;\n\n //! Preprocess the data for finding nearest neighbors by sorting into a\n //! KD-Tree. Note: all particle pointers are invalid after this call.\n virtual void sort()=0;\n\n //! Adds an attribute to the particle with the provided name, type and count\n virtual ParticleAttribute addAttribute(const char* attribute,ParticleAttributeType type,\n const int count)=0;\n\n //! Adds a fixed attribute with the provided name, type and count\n virtual FixedAttribute addFixedAttribute(const char* attribute,ParticleAttributeType type,\n const int count)=0;\n\n //! Add a particle to the particle set. Returns the offset to the particle\n virtual ParticleIndex addParticle()=0;\n\n //! Add a set of particles to the particle set. Returns the offset to the\n //! first particle\n virtual iterator addParticles(const int count)=0;\n\n //! Produce a beginning iterator for the particles\n iterator begin()\n {return setupIterator();}\n\n //! Produce a ending iterator for the particles\n iterator end()\n {return iterator();}\n\n //! Produce a const iterator\n virtual iterator setupIterator(const int index=0)=0;\n\nprivate:\n virtual void* dataInternal(const ParticleAttribute& attribute,const ParticleIndex particleIndex) const=0;\n virtual void* fixedDataInternal(const FixedAttribute& attribute) const=0;\n};\n\n//! Provides an empty particle instance, freed with p->release()\nParticlesDataMutable* create();\n\nParticlesDataMutable* createInterleave();\n\n//! Clone a ParticlesData instance into a new ParticlesDataMutable instance.\n//! This does *not* copy data, it only copies the attribute schema.\nParticlesDataMutable* cloneSchema(const ParticlesData&);\n\n//! Copy a ParticlesData instance into a new ParticlesDataMutable instance.\n//! clone() copies the detail attributes and particle data by default.\n//! To copy only the detail attributes, pass particles=false.\nParticlesDataMutable* clone(const ParticlesData&, bool particles=true);\n\n//! Provides read/write access to a particle set stored in a file\n//! freed with p->release()\nParticlesDataMutable* read(const char* filename,const bool verbose=true,std::ostream& errorStream=std::cerr);\n\n//! Provides read access to a particle headers (number of particles\n//! and attribute information, much cheapeer\nParticlesInfo* readHeaders(const char* filename,const bool verbose=true,std::ostream& errorStream=std::cerr);\n\n//! Provides access to a particle set stored in a file\n//! if filename ends with .gz or forceCompressed is true, the file is compressed.\nvoid write(const char* filename,const ParticlesData&,const bool forceCompressed=false,bool verbose=true,std::ostream& errorStream=std::cerr);\n\n//! Cached (only one copy) read only way to read a particle file\n/*!\n Loads a file read-only if not already in memory, otherwise returns\n already loaded item. Pointer is owned by Partio and must be released\n with p->release(); (will not be deleted if others are also holding).\n If you want to do finding neighbors give true to sort\n*/\nParticlesData* readCached(const char* filename,const bool sort,const bool verbose=true,std::ostream& errorStream=std::cerr);\n\n//! Begin accessing data in a cached file\n/*!\n Indicates to Partio that data access from a cached particle set will\n start. The sent in particles pointer must be from a readCached()\n call, not from read() or create(). Attributes can be read before this call.\n*/\nvoid beginCachedAccess(ParticlesData* particles);\n\n//! End accessing data in a cached file\n/*!\n Indicates to Partio that data from a cached particle read will\n end. The sent in particles pointer must be from a readCached()\n call, not from read() or create(). This allows the particle API\n to free all data pages, if they are needed.\n*/\nvoid endCachedAccess(ParticlesData* particles);\n\n//! Prints a subset of particle data in a textual form\nvoid print(const ParticlesData* particles);\n\nParticlesDataMutable* computeClustering(ParticlesDataMutable* particles, const int numNeighbors,const double radiusSearch,const double radiusInside,const int connections,const double density);\n\n//! Merges one particle set into another\n/*!\n Given a ParticleSetMutable, merges it with a second ParticleSet,\n copying particles and attributes that align with the base particle\n set. If an identifier is provided, that will be used as a key\n to replace the particle in the base set with the particle in the second\n set with the same identifier attribute value. If the identifier is not\n provided or the particle's attribute value is not found in the base set,\n a new particle is added. If used, the identifier must be a single INT.\n*/\nvoid merge(ParticlesDataMutable& base, const ParticlesData& delta, const std::string& identifier=std::string());\n\n}\n#endif\n" }, { "path": "Externals/partio/PartioAttribute.h", "content": "/*\nPARTIO SOFTWARE\nCopyright 2010 Disney Enterprises, Inc. All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n*/\n\n/*!\n The interface of the particle API (Partio)\n what type the primitive is, how many instances of the primitive there, name of\n the attribute and an index which speeds lookups of data\n*/\n\n#ifndef _PartioParticleAttribute_h_\n#define _PartioParticleAttribute_h_\nnamespace Partio{\n\n// Particle Types\nenum ParticleAttributeType {NONE=0,VECTOR=1,FLOAT=2,INT=3,INDEXEDSTR=4};\n\ntemplate struct ETYPE_TO_TYPE\n{struct UNUSABLE;typedef UNUSABLE TYPE;};\ntemplate<> struct ETYPE_TO_TYPE{typedef float TYPE;};\ntemplate<> struct ETYPE_TO_TYPE{typedef float TYPE;};\ntemplate<> struct ETYPE_TO_TYPE{typedef int TYPE;};\ntemplate<> struct ETYPE_TO_TYPE{typedef int TYPE;};\n\ntemplate struct\nIS_SAME{static const bool value=false;};\ntemplate struct IS_SAME{static const bool value=true;};\n\ntemplate bool\ntypeCheck(const ParticleAttributeType& type)\n{\n // if T is void, don't bother checking what we passed in\n if (IS_SAME::value) return true;\n switch(type){\n case VECTOR: return IS_SAME::TYPE,T>::value;\n case FLOAT: return IS_SAME::TYPE,T>::value;\n case INT: return IS_SAME::TYPE,T>::value;\n case INDEXEDSTR: return IS_SAME::TYPE,T>::value;\n default: return false; // unknown type\n }\n}\n\ninline \nint TypeSize(ParticleAttributeType attrType)\n{\n switch(attrType){\n case NONE: return 0;\n case VECTOR: return sizeof(float);\n case FLOAT: return sizeof(float);\n case INT: return sizeof(int);\n case INDEXEDSTR: return sizeof(int);\n default: return 0;\n }\n}\n\nstd::string TypeName(ParticleAttributeType attrType);\n\n// Particle Attribute Specifier\n//! Particle Collection Interface\n/*!\n This class provides a handle and description of an attribute. This includes\n what type the primitive is, the number of entries, the name of\n the attribute and an index which speeds lookups of data\n*/\nclass ParticleAttribute\n{\npublic:\n //! Type of attribute\n ParticleAttributeType type;\n\n //! Number of entries, should be 3 if type is VECTOR\n int count;\n\n //! Name of attribute\n std::string name;\n\n //! Internal method of fast access, user should not use or change\n int attributeIndex;\n\n //! Comment used by various data/readers for extra attribute information\n //! for example for a PTC file to read and write this could be \"color\" or \"point\"\n // std::string comment;\n};\n\n// Fixed Attribute Specifier\n//! Fixed Attribute Interface\n/*!\n This class provides a handle and description of an attribute. This includes\n what type the primitive is, the number of entries, the name of\n the attribute and an index which speeds lookups of data\n*/\nclass FixedAttribute\n{\npublic:\n //! Type of attribute\n ParticleAttributeType type;\n\n //! Number of entries, should be 3 if type is VECTOR\n int count;\n\n //! Name of attribute\n std::string name;\n\n //! Internal method of fast access, user should not use or change\n int attributeIndex;\n\n //! Comment used by various data/readers for extra attribute information\n //! for example for a PTC file to read and write this could be \"color\" or \"point\"\n // std::string comment;\n};\n}\n#endif\n" }, { "path": "Externals/partio/PartioIterator.h", "content": "/*\nPARTIO SOFTWARE\nCopyright 2010 Disney Enterprises, Inc. All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n*/\n#ifndef _PartioParticleIterator_h_\n#define _PartioParticleIterator_h_\n\n#include \n#include \n#include \n#include \"PartioAttribute.h\"\n\nnamespace Partio{\n\nclass ParticlesData;\nstruct ParticleAccessor;\n\n//! Data\n/*!\n This class represents a piece of data stored in a particle attribute.\n The only allowed values are float and d\n*/\ntemplate\nstruct Data\n{\n T x[d];\n\n const T& operator[](const int i) const {return x[i];}\n T& operator[](const int i) {return x[i];}\n};\ntypedef Data DataI;\ntypedef Data DataF;\ntypedef Data DataV;\n\n\ntemplate class ParticleIterator;\n\nstruct Provider\n{\n virtual void setupIteratorNextBlock(ParticleIterator& iterator) const=0;\n virtual void setupIteratorNextBlock(ParticleIterator& iterator)=0;\n virtual void setupAccessor(ParticleIterator& iterator,ParticleAccessor& accessor) const=0;\n virtual void setupAccessor(ParticleIterator& iterator,ParticleAccessor& accessor)=0;\n virtual ~Provider(){}\n};\n\ntemplate\nstruct PROVIDER\n{\n typedef Provider TYPE;\n};\ntemplate<>\nstruct PROVIDER\n{\n typedef const Provider TYPE;\n};\n\n// TODO: non copyable\nstruct ParticleAccessor\n{\n int stride;\n char* basePointer;\n int attributeIndex; // index of attribute opaque, do not touch\n int count;\nprivate:\n ParticleAttributeType type;\n \n ParticleAccessor* next;\n\npublic:\n ParticleAccessor(const ParticleAttribute& attr)\n :stride(0),basePointer(0),attributeIndex(attr.attributeIndex),\n count(attr.count),type(attr.type),next(0)\n {}\n\n template TDATA* raw(const TITERATOR& it)\n {return reinterpret_cast(basePointer+it.index*stride);}\n\n template const TDATA* raw(const TITERATOR& it) const\n {return reinterpret_cast(basePointer+it.index*stride);}\n\n template TDATA& data(const TITERATOR& it)\n {return *reinterpret_cast(basePointer+it.index*stride);}\n\n template const TDATA& data(const TITERATOR& it) const\n {return *reinterpret_cast(basePointer+it.index*stride);}\n\n friend class ParticleIterator;\n friend class ParticleIterator;\n};\n\n\ntemplate\nclass ParticleIterator\n{\npublic:\nprivate:\n typedef typename PROVIDER::TYPE PROVIDER;\n\n //! Delegate, null if the iterator is false\n PROVIDER* particles;\n\npublic:\n //! Start of non-interleaved index of contiguous block\n size_t index;\nprivate:\n\n //! End of non-interleaved index of contiguous block\n size_t indexEnd;\n\n //! This is used for both non-interleaved and interleaved particle attributes\n ParticleAccessor* accessors;\n\npublic:\n //! Construct an invalid iterator\n ParticleIterator()\n :particles(0),index(0),indexEnd(0),accessors(0)\n {}\n\n //! Copy constructor. NOTE: Invalidates any accessors that have been registered with it\n ParticleIterator(const ParticleIterator& other)\n\t\t:particles(other.particles),index(other.index),indexEnd(other.indexEnd),accessors(0)\n {}\n\n //! Construct an iterator with iteration parameters. This is typically only\n //! called by implementations of Particle (not by users). For users, use\n //! begin() and end() on the particle type\n ParticleIterator(PROVIDER* particles,size_t index,size_t indexEnd)\n :particles(particles),index(index),indexEnd(indexEnd)\n {}\n\n //! Whether the iterator is valid\n bool valid() const\n {return particles;}\n\n //! Increment the iterator (postfix). Prefer the prefix form below to this one.\n ParticleIterator operator++(int)\n {\n ParticleIterator newIt(*this);\n index++;\n return newIt;\n }\n\n //! Increment the iterator (prefix).\n ParticleIterator& operator++()\n {\n index++;\n // TODO: make particles==0 check unnecessary by using indexEnd=0 to signify invalid iterator\n if((index>indexEnd) && particles) particles->setupIteratorNextBlock(*this);\n return *this;\n }\n\n //! Iterator comparison equals\n bool operator==(const ParticleIterator& other)\n {\n // TODO: this is really really expensive\n // TODO: this needs a block or somethingt o say which segment it is\n return particles==other.particles && index==other.index;\n }\n \n //! Iterator comparison not-equals\n bool operator!=(const ParticleIterator& other)\n {\n if(other.particles!=particles) return true; // if not same delegate\n else if(particles==0) return false; // if both are invalid iterators\n else return !(*this==other);\n }\n \n void addAccessor(ParticleAccessor& newAccessor)\n {\n newAccessor.next=accessors;\n accessors=&newAccessor;\n if(particles) particles->setupAccessor(*this,newAccessor);\n }\n\n\n // TODO: add copy constructor that wipes out accessor linked list\n\n};\n\ntemplate\nstd::ostream& operator<<(std::ostream& output,const Data& v)\n{\n output<\n#include \n#include \n\nnamespace Partio{\n\nclass Vec3\n{\npublic:\n float x,y,z;\n\n inline Vec3()\n :x(0),y(0),z(0)\n {}\n\n inline Vec3(const float x,const float y,const float z)\n :x(x),y(y),z(z)\n {}\n\n inline Vec3(const float v[3])\n :x(v[0]),y(v[1]),z(v[2])\n {}\n\n inline float length()\n {return std::sqrt(x*x+y*y+z*z);}\n\n inline float normalize()\n {float l=length();x/=l;y/=l;z/=l;return l;}\n\n inline Vec3 normalized() const\n {Vec3 foo(x,y,z);foo.normalize();return foo;}\n\n inline Vec3 operator*(const float a) const\n {return Vec3(a*x,a*y,a*z);}\n\n inline Vec3 operator-(const Vec3& v) const\n {return Vec3(x-v.x,y-v.y,z-v.z);}\n\n inline Vec3 operator+(const Vec3& v) const\n {return Vec3(x+v.x,y+v.y,z+v.z);}\n\n inline Vec3 operator+=(const Vec3& v)\n {x+=v.x;y+=v.y;z+=v.z;return *this;}\n\n inline Vec3 cross(const Vec3& v) const\n {Vec3 ret(y*v.z-z*v.y,z*v.x-x*v.z,x*v.y-y*v.x);return ret;}\n\n inline Vec3 min(const Vec3& v) const\n {\n return Vec3(std::min(x,v.x),std::min(y,v.y),std::min(z,v.z));\n }\n\n inline Vec3 max(const Vec3& v) const\n {\n return Vec3(std::max(x,v.x),std::max(y,v.y),std::max(z,v.z));\n }\n};\n\n\ninline std::ostream& operator<<(std::ostream& stream,const Vec3& v)\n{return stream<\n#elif defined(__GNUC__)\n#include \n#endif\n\nnamespace Partio\n{\n\n/* balanced kdtree\n Brent Burley, Mar 2006\n\n The tree is left-balanced (i.e. the left subtree is always\n complete). The nodes are stored in traversal order (\"pre-order\")\n to optimize memory lookahead and cache-coherence during traversal.\n\n This means that:\n 1) The root node is node 0, depth 0.\n 2) Any given subtree is stored in a contiguous memory block.\n 3) The left child of node n is node n+1.\n 4) The right child of node n is node n+(size of left subtree).\n 5) The size of the left subtree of any node can be easily\n determined based on the node's overall subtree size (left+right+1).\n This can be propagated down during traversal.\n*/\n\n#include \n#include \n#include \n#include \n#include \n\ntemplate class BBox\n{\n public:\n float min[k];\n float max[k];\n\n BBox() { clear(); }\n BBox(const float p[k]) { set(p); }\n\n void set(const float p[k])\n {\n\tfor (int i = 0; i < k; i++) {\n\t min[i] = max[i] = p[i];\n\t}\n }\n\n void clear()\n {\n\tfor (int i = 0; i < k; i++) {\n\t min[i] = FLT_MAX;\n\t max[i] = FLT_MIN;\n\t}\n }\n\n\n void grow(const float p[k])\n {\n\tfor (int i = 0; i < k; i++) {\n\t if (p[i] < min[i]) min[i] = p[i];\n\t if (p[i] > max[i]) max[i] = p[i];\n\t}\n }\n\n void grow(float R)\n {\n\tfor (int i = 0; i < k; i++) {\n\t min[i] -= R;\n\t max[i] += R;\n\t}\n }\n\n void grow(const BBox& b)\n {\n\tfor (int i = 0; i < k; i++) {\n\t if (b.min[i] < min[i]) min[i] = b.min[i];\n\t if (b.max[i] > max[i]) max[i] = b.max[i];\n\t}\n }\n\n bool intersects(const BBox& b) const\n {\n\tfor (int i = 0; i < k; i++) {\n\t if (b.max[i] < min[i] || b.min[i] > max[i]) return 0;\n\t}\n\treturn 1;\n }\n\n bool inside(const float p[k]) const\n {\n\tfor (int i = 0; i < k; i++) {\n\t if (p[i] < min[i] || p[i] > max[i]) return 0;\n\t}\n\treturn 1;\n }\n};\n\n\n// MAKE-heap on a binary (array based) heap\n// loosely based on Henrik Wann Jensen's Photon Mapping book, but made 0-indexed\n// and commented\ninline float buildHeap(uint64_t *result, float *distance_squared,int heap_size)\n{\n int max_non_leaf_index=heap_size/2-1; // 0 to max_non_leaf_index is indices of parents\n\n // go from bottom of tree scanning right to left in each height of the tree\n for(int subtreeParent=max_non_leaf_index;subtreeParent>=0;subtreeParent--){\n int current_parent=subtreeParent;\n while(current_parent<=max_non_leaf_index){\n int left_index=2*current_parent+1;int right_index=2*current_parent+2;\n // find largest element\n int largest_index=current_parent;\n if(left_indexdistance_squared[largest_index])\n largest_index=left_index;\n if(right_indexdistance_squared[largest_index])\n largest_index=right_index;\n // subtree parented at current_parent satisfies heap property because parent has largest\n if(largest_index==current_parent) break;\n // pull large value up and descend to tree to see if new that subtree is invalid\n std::swap(result[largest_index],result[current_parent]);\n std::swap(distance_squared[largest_index],distance_squared[current_parent]);\n current_parent=largest_index;\n }\n }\n return distance_squared[0]; // return max distance\n}\n\n// Inserts smaller element into heap (does not check so caller must)\ninline float insertToHeap(uint64_t *result,float*distance_squared,int heap_size,int new_id,float new_distance_squared)\n{\n assert(new_distance_squared=heap_size) break;\n else if(right>=heap_size || distance_squared[left]>distance_squared[right]) index_of_largest=left;\n else index_of_largest=right;\n // new element is largest\n if(new_distance_squared>distance_squared[index_of_largest]) break;\n // pull the biggest element up and recurse to where it came from\n std::swap(result[index_of_largest],result[current_parent]);\n std::swap(distance_squared[index_of_largest],distance_squared[current_parent]);\n current_parent=index_of_largest;\n }\n // overwrite current node in tree\n distance_squared[current_parent]=new_distance_squared;\n result[current_parent]=new_id;\n return distance_squared[0]; // return max distance\n}\n\n\ntemplate class KdTree\n{\n\n struct NearestQuery\n {\n NearestQuery(uint64_t *result,float *distanceSquared,const float pquery_in[k],\n int maxPoints,float maxRadiusSquared)\n :result(result),distanceSquared(distanceSquared),maxPoints(maxPoints),\n foundPoints(0),maxRadiusSquared(maxRadiusSquared)\n\n {for(int i=0;i(_points.size()); }\n const BBox& bbox() const { return _bbox; }\n const float* point(int i) const { return _points[i].p; }\n uint64_t id(int i) const { return _ids[i]; }\n void setPoints(const float* p, int n);\n void sort();\n void findPoints(std::vector& points, const BBox& bbox) const;\n float findNPoints(std::vector& result,std::vector& distanceSquared,\n const float p[k],int nPoints,float maxRadius) const;\n int findNPoints(uint64_t *result,float *distanceSquared, float *finalSearchRadius2,\n const float p[k], int nPoints, float maxRadius) const;\n\n\n private:\n void sortSubtree(int n, int count, int j);\n struct ComparePointsById {\n\tfloat* points;\n\tComparePointsById(float* p) : points(p) {}\n\tbool operator() (uint64_t a, uint64_t b) { return points[a*k] < points[b*k]; }\n };\n void findPoints(std::vector& result, const BBox& bbox,\n\t\t int n, int size, int j) const;\n void findNPoints(NearestQuery& query,int n,int size,int j) const;\n\n static inline void ComputeSubtreeSizes(int size, int& left, int& right)\n {\n\t// if (size+1) is a power of two, then subtree is balanced\n\tbool balanced = ((size+1) & size) == 0;\n\tif (balanced) {\n\t // subtree size = (size-1)/2\n\t left = right = size>>1; // ignore -1 since size is always odd\n\t}\n\telse if (size == 2) {\n\t // special case\n\t left = 1;\n\t right = 0;\n\t}\n\telse {\n\t // left subtree size = (smallest power of 2 > half size)-1\n\t int i = 0;\n\t for (int c = size; c != 1; c >>= 1) i++;\n\t left = (1< _bbox;\n struct Point { float p[k]; };\n std::vector _points;\n std::vector _ids;\n bool _sorted;\n};\n\ntemplate \nKdTree::KdTree()\n : _sorted(0)\n{}\n\ntemplate \nKdTree::~KdTree()\n{}\n\n// TODO: this should take an array of ids in\ntemplate \nvoid KdTree::setPoints(const float* p, int n)\n{\n // copy points\n _points.resize(n);\n memcpy(&_points[0], p, sizeof(Point)*n);\n\n // compute bbox\n if (n) {\n\t_bbox.set(p);\n\tfor (int i = 1; i < n; i++)\n\t _bbox.grow(_points[i].p);\n } else _bbox.clear();\n\n // assign sequential ids\n _ids.resize(n);\n#if defined(__clang__) && defined(_LIBCPP_VERSION)\n std::iota(_ids.begin(), _ids.end(), 0);\n#elif defined(__GNUC__)\n __gnu_cxx::iota(_ids.begin(), _ids.end(), 0);\n#endif\n// _ids.reserve(n);\n// while ((int)_ids.size() < n) _ids.push_back(_ids.size());\n _sorted = 0;\n}\n\ntemplate \nvoid KdTree::sort()\n{\n if (_sorted) return;\n _sorted = 1;\n\n // reorder ids to sort points\n int np = static_cast(_points.size());\n if (!np) return;\n if (np > 1) sortSubtree(0, np, 0);\n\n // reorder points to match id order\n std::vector newpoints(np);\n for (int i = 0; i < np; i++)\n\tnewpoints[i] = _points[static_cast(_ids[i])];\n std::swap(_points, newpoints);\n}\n\ntemplate \nvoid KdTree::sortSubtree(int n, int size, int j)\n{\n int left, right; ComputeSubtreeSizes(size, left, right);\n\n // partition range [n, n+size) along axis j into two subranges:\n // [n, n+leftSize+1) and [n+leftSize+1, n+size)\n std::nth_element(&_ids[n], &_ids[n+left], &_ids[n+size],\n\t\t ComparePointsById(&_points[0].p[j]));\n // move median value (nth element) to front as root node of subtree\n std::swap(_ids[n], _ids[n+left]);\n\n // sort left and right subtrees using next discriminant\n if (left <= 1) return;\n#ifdef _MSC_VER \n #pragma warning (push) \n #pragma warning (disable : 4127) // suppress the warning due to the constant k being tested at runtime, an alternative would be to specialize the template class for k = 0\n#endif \n if (k > 1) j = (j+1)%k;\n#ifdef _MSC_VER \n #pragma warning (pop) \n#endif \n sortSubtree(n+1, left, j);\n if (right <= 1) return;\n sortSubtree(n+left+1, right, j);\n}\n\n\n\ntemplate \nfloat KdTree::findNPoints(std::vector& result,\n std::vector& distanceSquared,const float p[k],int nPoints,float maxRadius) const\n{\n result.resize(nPoints);\n distanceSquared.resize (nPoints);\n float finalRadius2 = maxRadius;\n int size = findNPoints (&result[0], &distanceSquared[0], &finalRadius2, p, nPoints, maxRadius);\n result.resize(size);\n distanceSquared.resize(size);\n return maxRadius;\n}\n\ntemplate \nint KdTree::findNPoints(uint64_t *result, float *distanceSquared, float *finalSearchRadius2,\n const float p[k],int nPoints,float maxRadius) const\n{\n float radius_squared=maxRadius*maxRadius;\n\n if (!size() || !_sorted || nPoints<1) return 0;\n\n NearestQuery query(result,distanceSquared,p,nPoints,radius_squared);\n findNPoints(query,0,size(),0);\n *finalSearchRadius2=query.maxRadiusSquared;\n return query.foundPoints;\n}\n\ntemplate\nvoid KdTree::findNPoints(typename KdTree::NearestQuery& query,int n,int size,int j) const\n{\n const float* p=&_points[n].p[0];\n\n if(size>1){\n float axis_distance=query.pquery[j]-p[j];\n int left,right;ComputeSubtreeSizes(size,left,right);\n int nextj=(j+1)%k;\n\n if(axis_distance>0){ // visit right definitely, and left if within distance\n if(right) findNPoints(query,n+left+1,right,nextj);\n if(axis_distance*axis_distance\nvoid KdTree::findPoints(std::vector& result, const BBox& bbox) const\n{\n if (!size() || !_sorted) return;\n if (!bbox.intersects(_bbox)) return;\n findPoints(result, bbox, 0, size(), 0);\n}\n\ntemplate \nvoid KdTree::findPoints(std::vector& result, const BBox& bbox,\n\t\t\t int n, int size, int j) const\n{\n // check point at n for inclusion\n const float* p = &_points[n].p[0];\n if (bbox.inside(p))\n\tresult.push_back(n);\n\n if (size == 1) return;\n\n // visit left subtree\n int left, right; ComputeSubtreeSizes(size, left, right);\n int nextj = (k > 1)? (j+1)%k : j;\n if (p[j] >= bbox.min[j])\n\tfindPoints(result, bbox, n+1, left, nextj);\n\n // visit right subtree\n if (right && p[j] <= bbox.max[j])\n\tfindPoints(result, bbox, n+left+1, right, nextj);\n}\n\n}\n#endif\n" }, { "path": "Externals/partio/core/Mutex.h", "content": "/*\nPARTIO SOFTWARE\nCopyright 2010 Disney Enterprises, Inc. All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n*/\n\n#ifndef _Mutex_\n#define _Mutex_\n\n#ifndef PARTIO_WIN32\n\n#include \n\nnamespace Partio\n{\n\n#ifndef PARTIO_USE_SPINLOCK\n\n class PartioMutex\n {\n pthread_mutex_t CacheLock;\n \n public:\n inline PartioMutex()\n {\n pthread_mutex_init(&CacheLock,0);\n }\n \n inline ~PartioMutex()\n {\n pthread_mutex_destroy(&CacheLock);\n }\n \n inline void lock()\n {\n pthread_mutex_lock(&CacheLock);\n }\n \n inline void unlock()\n {\n pthread_mutex_unlock(&CacheLock);\n }\n };\n \n#else\n\n class PartioMutex\n {\n pthread_spinlock_t CacheLock;\n \n public:\n inline PartioMutex()\n {\n pthread_spinlock_init(&CacheLock,PTHREAD_PROCESS_PRIVATE);\n }\n \n inline ~PartioMutex()\n {\n pthread_spinlock_destroy(&CacheLock);\n }\n \n inline void lock()\n {\n pthread_spinlock_lock(&CacheLock);\n }\n \n inline void unlock()\n {\n pthread_spinlock_unlock(&CacheLock);\n }\n };\n \n#endif // USE_PTHREAD_SPINLOCK\n}\n\n#else\n#include \n namespace Partio{\n\n class PartioMutex\n {\n HANDLE CacheLock;\n \n public:\n inline PartioMutex()\n {\n CacheLock=CreateMutex(0,FALSE,\"partiocache\");\n }\n \n inline ~PartioMutex()\n {\n CloseHandle(CacheLock);\n }\n \n inline void lock()\n {\n WaitForSingleObject(CacheLock,INFINITE);\n }\n \n inline void unlock()\n {\n ReleaseMutex(CacheLock);\n }\n };\n }\n#endif // USE_PTHREADS\n#endif // Header guard\n" }, { "path": "Externals/partio/core/Particle.cpp", "content": "/*\nPARTIO SOFTWARE\nCopyright 2010 Disney Enterprises, Inc. All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n*/\n#ifdef PARTIO_WIN32\n# define NOMINMAX\n#endif\n#define __STDC_LIMIT_MACROS\n#include \n#include \"ParticleSimple.h\"\n#include \"ParticleSimpleInterleave.h\"\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n\nnamespace Partio{\n\nstd::string\nTypeName(ParticleAttributeType attrType)\n{\n switch(attrType){\n case NONE: return \"NONE\";\n case VECTOR: return \"VECTOR\";\n case FLOAT: return \"FLOAT\";\n case INT: return \"INT\";\n case INDEXEDSTR: return \"INDEXEDSTR\";\n default: return 0;\n }\n}\n\nParticlesDataMutable*\ncreate()\n{\n return new ParticlesSimple;\n}\n\nParticlesDataMutable*\ncreateInterleave()\n{\n return new ParticlesSimpleInterleave;\n}\n\n\nParticlesDataMutable*\ncloneSchema(const ParticlesData& other)\n{\n ParticlesDataMutable* p = create();\n\n FixedAttribute detail;\n for(int i=0;iaddFixedAttribute(detail.name.c_str(), detail.type, detail.count);\n }\n\n ParticleAttribute attr;\n for(int j=0;jaddAttribute(attr.name.c_str(), attr.type, attr.count);\n }\n\n return p;\n}\n\nParticlesDataMutable*\nclone(const ParticlesData& other, bool particles)\n{\n ParticlesDataMutable* p = create();\n // Fixed attributes\n FixedAttribute srcFixedAttr, dstFixedAttr;\n for (int i(0), iend(other.numFixedAttributes()); i < iend; ++i) {\n other.fixedAttributeInfo(i, srcFixedAttr);\n\n dstFixedAttr = p->addFixedAttribute(\n srcFixedAttr.name.c_str(), srcFixedAttr.type, srcFixedAttr.count);\n assert(srcFixedAttr.type == dstFixedAttr.type);\n assert(srcFixedAttr.count == dstFixedAttr.count);\n // Register indexed strings\n if (srcFixedAttr.type == Partio::INDEXEDSTR) {\n const std::vector& values = other.fixedIndexedStrs(srcFixedAttr);\n for (int j = 0, jend = values.size(); j < jend; ++j) {\n p->registerFixedIndexedStr(dstFixedAttr, values[j].c_str());\n }\n }\n // Copy fixed data\n const void* src = other.fixedData(srcFixedAttr);\n void* dst = p->fixedDataWrite(dstFixedAttr);\n size_t size = Partio::TypeSize(dstFixedAttr.type) * dstFixedAttr.count;\n std::memcpy(dst, src, size);\n }\n if (!particles) {\n return p;\n }\n // Particle data\n Partio::ParticleAttribute srcAttr, dstAttr;\n const int numAttributes = other.numAttributes();\n const size_t numParticles = other.numParticles();\n std::vector dstAttrs;\n\n p->addParticles(numParticles);\n\n // We can't assume that the particle backend stores data contiguously, so\n // we copy one particle at a time. A bulk memcpy would be faster.\n for (int i = 0; i < numAttributes; ++i) {\n other.attributeInfo(i, srcAttr);\n // Register indexed strings\n if (srcAttr.type == Partio::INDEXEDSTR) {\n const std::vector& values = other.indexedStrs(srcAttr);\n for (int m = 0, mend = values.size(); m < mend; ++m) {\n p->registerIndexedStr(dstAttr, values[m].c_str());\n }\n }\n size_t size = Partio::TypeSize(srcAttr.type) * srcAttr.count;\n dstAttr = p->addAttribute(srcAttr.name.c_str(), srcAttr.type, srcAttr.count);\n\n for (Partio::ParticleIndex j = 0; j < numParticles; ++j) {\n const void *src = other.data(srcAttr, j);\n void *dst = p->dataWrite(dstAttr, j);\n std::memcpy(dst, src, size);\n }\n }\n\n return p;\n}\n\n\ntemplate void\nprintAttr(const ParticlesData* p,const ParticleAttribute& attr,const int particleIndex)\n{\n typedef typename ETYPE_TO_TYPE::TYPE TYPE;\n const TYPE* data=p->data(attr,particleIndex);\n for(int k=0;k\ngetAttrs(const ParticlesData& particles)\n{\n std::vector attrs(particles.numAttributes());\n for(int i=0;inumParticles()<numAttributes()< attrs = getAttrs(*particles);\n for (const ParticleAttribute& attr : attrs) {\n std::cout << \"attribute \" << attr.name\n << \" type=\" << TypeName(attr.type)\n << \" count=\" << attr.count << std::endl;\n }\n\n int numToPrint=std::min(10,particles->numParticles());\n std::cout<<\"num to print \"<begin(),end=particles->end();\n std::vector accessors;\n for(size_t k=0;k 1) std::cout<<\"(\";\n switch(attrs[k].type){\n case NONE:break;\n case FLOAT:\n case VECTOR:\n for(int c=0;c(it)[c];\n }\n break;\n case INT:\n for(int c=0;c(it)[c]<<\",\";\n }\n break;\n case INDEXEDSTR:\n for(int c=0;c(it)[c]<<\",\";\n }\n break;\n }\n if (attrs[k].count > 1) std::cout<<\")\";\n std::cout<<\"\\t\";\n }\n std::cout<> 11);\n seed ^= (seed << 7) & 0x9d2c5680UL;\n seed ^= (seed << 15) & 0xefc60000UL;\n seed ^= (seed >> 18);\n\n // permute\n static unsigned char p[256] = {\n 148,201,203,34,85,225,163,200,174,137,51,24,19,252,107,173,\n 110,251,149,69,180,152,141,132,22,20,147,219,37,46,154,114,\n 59,49,155,161,239,77,47,10,70,227,53,235,30,188,143,73,\n 88,193,214,194,18,120,176,36,212,84,211,142,167,57,153,71,\n 159,151,126,115,229,124,172,101,79,183,32,38,68,11,67,109,\n 221,3,4,61,122,94,72,117,12,240,199,76,118,5,48,197,\n 128,62,119,89,14,45,226,195,80,50,40,192,60,65,166,106,\n 90,215,213,232,250,207,104,52,182,29,157,103,242,97,111,17,\n 8,175,254,108,208,224,191,112,105,187,43,56,185,243,196,156,\n 246,249,184,7,135,6,158,82,130,234,206,255,160,236,171,230,\n 42,98,54,74,209,205,33,177,15,138,178,44,116,96,140,253,\n 233,125,21,133,136,86,245,58,23,1,75,165,92,217,39,0,\n 218,91,179,55,238,170,134,83,25,189,216,100,129,150,241,210,\n 123,99,2,164,16,220,121,139,168,64,190,9,31,228,95,247,\n 244,81,102,145,204,146,26,87,113,198,181,127,237,169,28,93,\n 27,41,231,248,78,162,13,186,63,66,131,202,35,144,222,223};\n union {\n uint32_t i;\n unsigned char c[4];\n } u1, u2;\n u1.i = seed;\n u2.c[3] = p[u1.c[0]];\n u2.c[2] = p[(u1.c[1]+u2.c[3])&0xff];\n u2.c[1] = p[(u1.c[2]+u2.c[2])&0xff];\n u2.c[0] = p[(u1.c[3]+u2.c[1])&0xff];\n\n // scale to [0.0 .. 1.0]\n return u2.i * (1.0/UINT32_MAX);\n}\n\nstruct IdAndIndex {\n IdAndIndex(int id, int index) : _id(id), _index(index) {}\n int _id, _index;\n bool operator<(const IdAndIndex &other) const {\n return _id < other._id;\n }\n};\n\ntemplate T smoothstep(T t){return (3.-2.*t)*t*t;}\n\nvoid addClusterAttribute(ParticlesDataMutable* cluster, ParticleAttribute& clusterAttribute, const ParticlesDataMutable* particle, const int index, const ParticleAttribute& attribute, const int neighborIndex, const std::vector >& indexAndInterp)\n{\n switch(attribute.type){\n case Partio::VECTOR:\n case Partio::FLOAT:\n {\n float* data = particle->dataWrite(attribute,index);\n float* neighborData = particle->dataWrite(attribute,neighborIndex);\n for (size_t i=0; idataWrite(clusterAttribute,indexAndInterp[i].first);\n for (int j=0; jdataWrite(attribute,index);\n for (size_t i=0; idataWrite(clusterAttribute,indexAndInterp[i].first);\n for (int j=0; j attributes;\n std::vector clusterAttributes;\n for (int i=0; inumAttributes(); i++) {\n ParticleAttribute attr;\n if (particles->attributeInfo(i,attr)) {\n if (attr.type == Partio::NONE) continue;\n attributes.push_back(attr);\n clusterAttributes.push_back(cluster->addAttribute(attributes[i].name.c_str(),attributes[i].type,attributes[i].count));\n if (attr.type == Partio::INDEXEDSTR) {\n const std::vector& strings = particles->indexedStrs(attr);\n for (size_t j=0; jregisterIndexedStr(clusterAttributes.back(),strings[j].c_str());\n }\n }\n if (attr.name == \"position\") {\n posAttr = attr;\n hasPosAttr = true;\n } else if (attr.name == \"id\") {\n idAttr = attr;\n hasIdAttr = true;\n }\n }\n }\n if (!hasPosAttr || (posAttr.type != VECTOR && posAttr.type != FLOAT) || posAttr.count !=3) {\n cluster->release();\n return 0;\n }\n if (!hasIdAttr || idAttr.type != INT || idAttr.count != 1) {\n cluster->release();\n return 0;\n }\n particles->sort();\n ParticleAttribute clusterIdAttr = cluster->addAttribute(\"clusterId\", Partio::INT, 1);\n for (int index=0; indexnumParticles(); index++) {\n const float* center=particles->data(posAttr,index);\n Vec3 position(center[0], center[1], center[2]);\n int id = particles->data(idAttr,index)[0];\n double radius = std::max(0., radiusInside);\n radius = std::min(100., radiusInside);\n double innerRadius = .01 * radius * radiusSearch;\n double invRadius = 1 / (radiusSearch - innerRadius);\n\n std::vector points;\n std::vector distSq;\n particles->findNPoints(center, numNeighbors, radiusSearch, points, distSq);\n\n std::vector idAndIndex;\n idAndIndex.reserve(points.size());\n idAndIndex.push_back(IdAndIndex(id, 0));\n for (unsigned int i = 0; i < points.size(); i++) {\n const int pointid = particles->data(idAttr,points[i])[0];\n if (pointid != id) idAndIndex.push_back(IdAndIndex(pointid, points[i]));\n }\n std::sort(++idAndIndex.begin(), idAndIndex.end());\n\n std::vector > originalPoint;\n originalPoint.push_back(std::make_pair(cluster->addParticle(),0.0f));\n int clusterId = 0;\n cluster->dataWrite(clusterIdAttr,originalPoint.back().first)[0] = clusterId++;\n for (size_t j = 0; j < attributes.size(); j++) {\n addClusterAttribute(cluster, clusterAttributes[j], particles, index, attributes[j], 0, originalPoint);\n }\n\n double hashArgs[3];\n hashArgs[0] = id;\n\n int foundConnections = std::min((int) idAndIndex.size(), connections+1);\n for (int i = 1; i < foundConnections; i++) {\n const float* neighbor=particles->data(posAttr,idAndIndex[i]._index);\n Vec3 neighborPosition(neighbor[0], neighbor[1], neighbor[2]);\n Vec3 dir = neighborPosition - position;\n\n // calculate number of instances based on density\n int numInstances = 0;\n double len = dir.length();\n if (len < innerRadius) {\n numInstances = density * len;\n } else {\n numInstances = density * len * smoothstep(1.-(len-innerRadius)*invRadius);\n }\n std::vector > indexAndInterp;\n for (int j = 0; j < numInstances; j++) {\n hashArgs[1] = idAndIndex[i]._id;\n hashArgs[2] = j;\n indexAndInterp.push_back(std::make_pair(cluster->addParticle(),static_cast(hash(3,hashArgs))));\n cluster->dataWrite(clusterIdAttr,indexAndInterp.back().first)[0] = clusterId++;\n }\n for (size_t j = 0; j < attributes.size(); j++) {\n addClusterAttribute(cluster, clusterAttributes[j], particles, index, attributes[j], idAndIndex[i]._index, indexAndInterp);\n }\n }\n }\n return cluster;;\n}\n\ntemplate\nstruct AttributePair {\n T base;\n T delta;\n};\n\nvoid merge(ParticlesDataMutable& base, const ParticlesData& delta, const std::string& identifier)\n{\n // Build a map from the identifier value to the particle index\n // and locate the identifier attribute in the base.\n // This assumes unique identifiers per particle.\n std::unordered_map idToParticleIndex;\n ParticleAttribute baseIdAttr;\n bool baseHasIdentifier = base.attributeInfo(identifier.c_str(), baseIdAttr);\n if (baseHasIdentifier) {\n if (baseIdAttr.type == INT) {\n for (int i=0; i(baseIdAttr,i)[0]] = i;\n }\n } else {\n baseHasIdentifier = false;\n }\n }\n\n // Locate the identifier attribute in the delta\n ParticleAttribute deltaIdAttr;\n bool deltaHasIdentifier = delta.attributeInfo(identifier.c_str(), deltaIdAttr);\n if (deltaHasIdentifier) {\n deltaHasIdentifier &= deltaIdAttr.type == INT;\n }\n bool hasIdentifier = baseHasIdentifier && deltaHasIdentifier;\n\n // Identify the attributes to be copied (base present in delta)\n std::vector> attrs;\n std::vector indexStrAttrs; /* indexes into attrs */\n for (int i=0; i({std::move(baseAttr), std::move(deltaAttr)}));\n }\n }\n\n // Identify the attributes to be added (in delta, not present in base)\n double empty[16]{0};\n for (int i=0; i({std::move(baseAttr), std::move(deltaAttr)}));\n\n // Set the attribute to a default value in the base particle set\n for (int p=0; p(deltaAttr);\n base.setFixed(baseAttr, src);\n }\n }\n\n // Identify fixed attributes to extend\n for (int i=0; i(deltaAttr);\n base.setFixed(baseAttr, src);\n }\n }\n\n // Merge the indexed strings. If the delta holds new strings for the same attribute,\n // we have to re-index it and extend the base string list with the new strings.\n // If the string exists in both, we still have to map the delta index to the base index.\n std::unordered_map > stringToString;\n for (size_t index : indexStrAttrs) {\n const AttributePair& attr = attrs[index];\n\n /* For each string in the delta, add to base if missing. And re-index. */\n const std::vector& baseStrs = base.indexedStrs(attr.base);\n // Map source indices name->index for faster searching\n std::unordered_map indexInBase;\n for (size_t i=0; i& deltaStrs = delta.indexedStrs(attr.delta);\n for (size_t i=0; isecond;\n } else {\n int newIndex = base.registerIndexedStr(attr.base, deltaStr.c_str());\n stringToString[attr.base.name][i] = newIndex;\n }\n }\n }\n\n\n // Loop through the delta particles and incorporate into the base\n for (int i=0; i(deltaIdAttr, i));\n auto it = idToParticleIndex.find(idValue);\n if (it != idToParticleIndex.end()) {\n index = it->second;\n }\n }\n if (index == -1) {\n index = base.addParticle();\n }\n\n // Copy the attributes to the new/overridden particle\n for (const AttributePair& attr : attrs) {\n size_t size = Partio::TypeSize(attr.base.type) * attr.base.count;\n void *dst = base.dataWrite(attr.base, index);\n const void* src;\n std::unique_ptr newIndices;\n if (attr.base.type == INDEXEDSTR) {\n newIndices.reset(new int[attr.base.count]);\n const int* indices = delta.data(attr.delta, i);\n for (int j=0; j(attr.delta, i);\n }\n std::memcpy(dst, src, size);\n }\n }\n}\n\n}\n" }, { "path": "Externals/partio/core/ParticleCaching.cpp", "content": "/*\nPARTIO SOFTWARE\nCopyright 2010 Disney Enterprises, Inc. All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n*/\n#include \n#include \n#include \"Mutex.h\"\n#include \"../Partio.h\"\n\n//#####################################################################\nnamespace Partio{\n\nnamespace\n{\n static PartioMutex mutex;\n}\n \n// cached read write\nstd::map cachedParticlesCount;\nstd::map cachedParticles;\n\nParticlesData* readCached(const char* filename,const bool sort,const bool verbose,std::ostream& error)\n{\n mutex.lock();\n std::map::iterator i=cachedParticles.find(filename);\n\n ParticlesData* p=0;\n if(i!=cachedParticles.end()){\n p=i->second;\n cachedParticlesCount[p]++;\n }else{\n ParticlesDataMutable* p_rw=read(filename,verbose);\n if(p_rw){\n if(sort) p_rw->sort();\n p=p_rw;\n cachedParticles[filename]=p;\n cachedParticlesCount[p]=1;\n }\n }\n mutex.unlock();\n return p;\n}\n\nvoid freeCached(ParticlesData* particles)\n{\n if(!particles) return;\n\n mutex.lock();\n\n std::map::iterator i=cachedParticlesCount.find(particles);\n if(i==cachedParticlesCount.end()){ // Not found in cache, just free\n delete particles;\n }else{ // found in cache\n i->second--; // decrement ref count\n if(i->second==0){ // ref count is now zero, remove from structure\n delete particles;\n cachedParticlesCount.erase(i);\n for(std::map::iterator i2=cachedParticles.begin();\n i2!=cachedParticles.end();++i2){\n if(i2->second==particles){\n cachedParticles.erase(i2);\n goto exit_and_release;\n }\n } \n assert(false);\n }\n }\n exit_and_release:\n mutex.unlock();\n}\n\nvoid beginCachedAccess(ParticlesData*)\n{\n // TODO: for future use\n}\n\nvoid endCachedAccess(ParticlesData*)\n{\n // TODO: for future use\n}\n\n} // namespace Partio\n" }, { "path": "Externals/partio/core/ParticleCaching.h", "content": "/*\nPARTIO SOFTWARE\nCopyright 2010 Disney Enterprises, Inc. All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n*/\n\n#ifndef _ParticleCaching_h_\n#define _ParticleCaching_h_\n\nnamespace Partio{\nclass Particles;\nvoid freeCached(ParticlesInfo* particles);\n}\n\n#endif\n" }, { "path": "Externals/partio/core/ParticleHeaders.cpp", "content": "/*\nPARTIO SOFTWARE\nCopyright 2010 Disney Enterprises, Inc. All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n*/\n#include \"ParticleHeaders.h\"\n#include \n#include \n#include \n#include \n\nusing namespace Partio;\n\nParticleHeaders::\nParticleHeaders()\n :particleCount(0)\n{\n}\n\nParticleHeaders::\n~ParticleHeaders()\n{\n}\n\nvoid ParticleHeaders::\nrelease()\n{\n delete this;\n}\n\nint ParticleHeaders::\nnumParticles() const\n{\n return particleCount;\n}\n\nint ParticleHeaders::\nnumAttributes() const\n{\n return static_cast(attributes.size());\n}\n\nint ParticleHeaders::\nnumFixedAttributes() const\n{\n return static_cast(fixedAttributes.size());\n}\n\nbool ParticleHeaders::\nattributeInfo(const int attributeIndex,ParticleAttribute& attribute) const\n{\n if(attributeIndex<0 || attributeIndex>=(int)attributes.size()) return false;\n attribute=attributes[attributeIndex];\n return true;\n}\n\nbool ParticleHeaders::\nfixedAttributeInfo(const int attributeIndex,FixedAttribute& attribute) const\n{\n if(attributeIndex<0 || attributeIndex>=(int)fixedAttributes.size()) return false;\n attribute=fixedAttributes[attributeIndex];\n return true;\n}\n\nbool ParticleHeaders::\nattributeInfo(const char* attributeName,ParticleAttribute& attribute) const\n{\n std::map::const_iterator it=nameToAttribute.find(attributeName);\n if(it!=nameToAttribute.end()){\n attribute=attributes[it->second];\n return true;\n }\n return false;\n}\n\nbool ParticleHeaders::\nfixedAttributeInfo(const char* attributeName,FixedAttribute& attribute) const\n{\n std::map::const_iterator it=nameToFixedAttribute.find(attributeName);\n if(it!=nameToFixedAttribute.end()){\n attribute=fixedAttributes[it->second];\n return true;\n }\n return false;\n}\n\nvoid ParticleHeaders::\nsort()\n{\n assert(false);\n}\n\n\nint ParticleHeaders::\nregisterIndexedStr(const ParticleAttribute&, const char*)\n{\n assert(false);\n return -1;\n}\n\nint ParticleHeaders::\nregisterFixedIndexedStr(const FixedAttribute&, const char* str)\n{\n assert(false);\n return -1;\n}\n\nint ParticleHeaders::\nlookupIndexedStr(const ParticleAttribute&, const char*) const\n{\n assert(false);\n return -1;\n}\n\nint ParticleHeaders::\nlookupFixedIndexedStr(const FixedAttribute&, const char* str) const\n{\n assert(false);\n return -1;\n}\n\nconst std::vector& ParticleHeaders::\nindexedStrs(const ParticleAttribute&) const\n{\n static std::vector dummy;\n assert(false);\n return dummy;\n}\n\nconst std::vector& ParticleHeaders::\nfixedIndexedStrs(const FixedAttribute& attr) const\n{\n static std::vector dummy;\n assert(false);\n return dummy;\n}\n\nvoid ParticleHeaders::\nfindPoints(const float[3],const float[3],std::vector&) const\n{\n assert(false);\n}\n\nfloat ParticleHeaders::\nfindNPoints(const float[3],const int,const float,std::vector&,std::vector&) const\n{\n assert(false);\n return 0;\n}\n\nint ParticleHeaders::\nfindNPoints(const float[3],int,const float, ParticleIndex *,\n float *, float *) const\n{\n assert(false);\n return 0;\n}\n\nParticleAttribute ParticleHeaders::\naddAttribute(const char* attribute,ParticleAttributeType type,const int count)\n{\n // TODO: check if attribute already exists and if so what data type\n ParticleAttribute attr;\n attr.name=attribute;\n attr.type=type;\n attr.attributeIndex=static_cast(attributes.size()); // all arrays separate so we don't use this here!\n attr.count=count;\n attributes.push_back(attr);\n nameToAttribute[attribute]=static_cast(attributes.size()-1);\n return attr;\n}\n\nFixedAttribute ParticleHeaders::\naddFixedAttribute(const char* attribute,ParticleAttributeType type,const int count)\n{\n // TODO: check if attribute already exists and if so what data type\n FixedAttribute attr;\n attr.name=attribute;\n attr.type=type;\n attr.attributeIndex=fixedAttributes.size(); // all arrays separate so we don't use this here!\n attr.count=count;\n fixedAttributes.push_back(attr);\n nameToFixedAttribute[attribute]=fixedAttributes.size()-1;\n return attr;\n}\n\nParticleIndex ParticleHeaders::\naddParticle()\n{\n ParticleIndex index=particleCount;\n particleCount++;\n return index;\n}\n\nParticlesDataMutable::iterator ParticleHeaders::\naddParticles(const int countToAdd)\n{\n particleCount+=countToAdd;\n return iterator();\n}\n\nvoid* ParticleHeaders::\ndataInternal(const ParticleAttribute&,const ParticleIndex) const\n{\n assert(false);\n return 0;\n}\n\nvoid* ParticleHeaders::\nfixedDataInternal(const FixedAttribute& attribute) const\n{\n assert(false);\n return 0;\n}\n\nvoid ParticleHeaders::\ndataInternalMultiple(const ParticleAttribute&,const int,\n const ParticleIndex*,const bool,char*) const\n{\n assert(false);\n}\n\nvoid ParticleHeaders::\ndataAsFloat(const ParticleAttribute&,const int,\n const ParticleIndex*,const bool,float*) const\n{\n assert(false);\n}\n\n\nvoid ParticleHeaders::\nsetIndexedStr(const ParticleAttribute& attribute,int indexedStringToken,const char* str){\n assert(false);\n}\n\nvoid ParticleHeaders::\nsetFixedIndexedStr(const FixedAttribute& attribute,int indexedStringToken,const char* str){\n assert(false);\n}\n" }, { "path": "Externals/partio/core/ParticleHeaders.h", "content": "/*\nPARTIO SOFTWARE\nCopyright 2010 Disney Enterprises, Inc. All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n*/\n#ifndef _ParticlesHeaders_h_\n#define _ParticlesHeaders_h_\n\n#include \"../Partio.h\"\nnamespace Partio{\n\nclass ParticleHeaders:public ParticlesDataMutable\n{\npublic:\n ParticleHeaders();\n virtual void release();\nprotected:\n virtual ~ParticleHeaders();\n\n int numAttributes() const;\n int numFixedAttributes() const;\n int numParticles() const;\n bool attributeInfo(const char* attributeName,ParticleAttribute& attribute) const;\n bool fixedAttributeInfo(const char* attributeName,FixedAttribute& attribute) const;\n bool attributeInfo(const int attributeInfo,ParticleAttribute& attribute) const;\n bool fixedAttributeInfo(const int attributeInfo,FixedAttribute& attribute) const;\n\n int registerIndexedStr(const ParticleAttribute& attribute,const char* str);\n int registerFixedIndexedStr(const FixedAttribute& attribute,const char* str);\n int lookupIndexedStr(const ParticleAttribute& attribute,const char* str) const;\n int lookupFixedIndexedStr(const FixedAttribute& attribute,const char* str) const;\n void setIndexedStr(const ParticleAttribute& attribute,int indexedStrHandle,const char* str);\n void setFixedIndexedStr(const FixedAttribute& attribute,int indexedStrHandle,const char* str);\n const std::vector& indexedStrs(const ParticleAttribute& attr) const;\n const std::vector& fixedIndexedStrs(const FixedAttribute& attr) const;\n\n virtual void dataAsFloat(const ParticleAttribute& attribute,const int indexCount,\n const ParticleIndex* particleIndices,const bool sorted,float* values) const;\n\n void sort();\n\n void findPoints(const float bboxMin[3],const float bboxMax[3],std::vector& points) const;\n float findNPoints(const float center[3],int nPoints,const float maxRadius,\n std::vector& points,std::vector& pointDistancesSquared) const;\n int findNPoints(const float center[3],int nPoints,const float maxRadius,\n ParticleIndex *points, float *pointDistancesSquared, float *finalRadius2) const;\n ParticlesDataMutable* computeClustering(const int numNeighbors,const double radiusSearch,const double radiusInside,const int connections,const double density)\n {assert(false); return nullptr;}\n\n ParticleAttribute addAttribute(const char* attribute,ParticleAttributeType type,const int count);\n FixedAttribute addFixedAttribute(const char* attribute,ParticleAttributeType type,const int count);\n ParticleIndex addParticle();\n iterator addParticles(const int count);\n\n const_iterator setupConstIterator(const int index=0) const\n {return const_iterator();}\n\n iterator setupIterator(const int index=0)\n {return iterator();}\n\nprivate:\n void* dataInternal(const ParticleAttribute& attribute,const ParticleIndex particleIndex) const;\n void* fixedDataInternal(const FixedAttribute& attribute) const;\n void dataInternalMultiple(const ParticleAttribute& attribute,const int indexCount,\n const ParticleIndex* particleIndices,const bool sorted,char* values) const;\n\nprivate:\n int particleCount;\n std::vector attributes;\n std::map nameToAttribute;\n std::vector fixedAttributes;\n std::map nameToFixedAttribute;\n};\n}\n#endif\n" }, { "path": "Externals/partio/core/ParticleSimple.cpp", "content": "/*\nPARTIO SOFTWARE\nCopyright 2010 Disney Enterprises, Inc. All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n*/\n\n#ifdef PARTIO_WIN32\n# define NOMINMAX\n#endif\n\n#include \"ParticleSimple.h\"\n#include \"ParticleCaching.h\"\n#include \n#include \n#include \n#include \n\n#include \"KdTree.h\"\n\n\nusing namespace Partio;\n\nParticlesSimple::\nParticlesSimple()\n :particleCount(0),allocatedCount(0),kdtree(0)\n{\n}\n\nParticlesSimple::\n~ParticlesSimple()\n{\n for(unsigned int i=0;i(attributes.size());\n}\n\nint ParticlesSimple::\nnumFixedAttributes() const\n{\n return fixedAttributes.size();\n}\n\nbool ParticlesSimple::\nattributeInfo(const int attributeIndex,ParticleAttribute& attribute) const\n{\n if(attributeIndex<0 || attributeIndex>=(int)attributes.size()) return false;\n attribute=attributes[attributeIndex];\n return true;\n}\n\nbool ParticlesSimple::\nfixedAttributeInfo(const int attributeIndex,FixedAttribute& attribute) const\n{\n if(attributeIndex<0 || attributeIndex>=(int)fixedAttributes.size()) return false;\n attribute=fixedAttributes[attributeIndex];\n return true;\n}\n\nbool ParticlesSimple::\nattributeInfo(const char* attributeName,ParticleAttribute& attribute) const\n{\n std::map::const_iterator it=nameToAttribute.find(attributeName);\n if(it!=nameToAttribute.end()){\n attribute=attributes[it->second];\n return true;\n }\n return false;\n}\n\nbool ParticlesSimple::\nfixedAttributeInfo(const char* attributeName,FixedAttribute& attribute) const\n{\n std::map::const_iterator it=nameToFixedAttribute.find(attributeName);\n if(it!=nameToFixedAttribute.end()){\n attribute=fixedAttributes[it->second];\n return true;\n }\n return false;\n}\n\nvoid ParticlesSimple::\nsort()\n{\n ParticleAttribute attr;\n bool foundPosition=attributeInfo(\"position\",attr);\n if(!foundPosition){\n std::cerr<<\"Partio: sort, Failed to find position in particle\"<data(attr,baseParticleIndex); // contiguous assumption used here\n KdTree<3>* kdtree_temp=new KdTree<3>();\n kdtree_temp->setPoints(data,numParticles());\n kdtree_temp->sort();\n\n kdtree_mutex.lock();\n // TODO: this is not threadsafe!\n if(kdtree) delete kdtree;\n kdtree=kdtree_temp;\n kdtree_mutex.unlock();\n}\n\nvoid ParticlesSimple::\nfindPoints(const float bboxMin[3],const float bboxMax[3],std::vector& points) const\n{\n if(!kdtree){\n std::cerr<<\"Partio: findPoints without first calling sort()\"< box(bboxMin);box.grow(bboxMax);\n\n int startIndex=static_cast(points.size());\n kdtree->findPoints(points,box);\n // remap points found in findPoints to original index space\n for(unsigned int i=startIndex;iid(static_cast(points[i]));\n }\n}\n\nfloat ParticlesSimple::\nfindNPoints(const float center[3],const int nPoints,const float maxRadius,std::vector& points,\n std::vector& pointDistancesSquared) const\n{\n if(!kdtree){\n std::cerr<<\"Partio: findNPoints without first calling sort()\"<& rawPoints=points;\n float maxDistance=kdtree->findNPoints(points,pointDistancesSquared,center,nPoints,maxRadius);\n // remap all points since findNPoints clears array\n for(unsigned int i=0;iid(static_cast(points[i]));\n points[i]=index;\n }\n return maxDistance;\n}\n\nint ParticlesSimple::\nfindNPoints(const float center[3],int nPoints,const float maxRadius, ParticleIndex *points,\n float *pointDistancesSquared, float *finalRadius2) const\n{\n if(!kdtree){\n std::cerr<<\"Partio: findNPoints without first calling sort()\"<findNPoints (points, pointDistancesSquared, finalRadius2, center, nPoints, maxRadius);\n // remap all points since findNPoints clears array\n for(int i=0; i < count; i++){\n ParticleIndex index = kdtree->id(static_cast(points[i]));\n points[i]=index;\n }\n return count;\n}\n\nParticleAttribute ParticlesSimple::\naddAttribute(const char* attribute,ParticleAttributeType type,const int count)\n{\n if(nameToAttribute.find(attribute) != nameToAttribute.end()){\n std::cerr<<\"Partio: addAttribute failed because attr '\"<(attributes.size()); // all arrays separate so we don't use this here!\n attr.count=count;\n attributes.push_back(attr);\n nameToAttribute[attribute]=static_cast(attributes.size()-1);\n\n int stride=TypeSize(type)*count;\n attributeStrides.push_back(stride);\n char* dataPointer=(char*)malloc((size_t)allocatedCount*(size_t)stride);\n attributeData.push_back(dataPointer);\n attributeOffsets.push_back(dataPointer-(char*)0);\n attributeIndexedStrs.push_back(IndexedStrTable());\n\n return attr;\n}\n\nFixedAttribute ParticlesSimple::\naddFixedAttribute(const char* attribute,ParticleAttributeType type,const int count)\n{\n if(nameToFixedAttribute.find(attribute) != nameToFixedAttribute.end()){\n std::cerr<<\"Partio: addFixedAttribute failed because attr '\"<allocatedCount){\n // TODO: this should follow 2/3 rule\n allocatedCount=allocatedCount+countToAdd;\n for(unsigned int i=0;i& iterator)\n{\n iterator=end();\n}\n\nvoid ParticlesSimple::\nsetupIteratorNextBlock(Partio::ParticleIterator& iterator) const\n{\n iterator=ParticlesData::end();\n}\n\n\nvoid ParticlesSimple::\nsetupAccessor(Partio::ParticleIterator&,ParticleAccessor& accessor)\n{\n accessor.stride=accessor.count*sizeof(float);\n accessor.basePointer=attributeData[accessor.attributeIndex];\n}\n\nvoid ParticlesSimple::\nsetupAccessor(Partio::ParticleIterator&,ParticleAccessor& accessor) const\n{\n accessor.stride=accessor.count*sizeof(float);\n accessor.basePointer=attributeData[accessor.attributeIndex];\n}\n\nvoid* ParticlesSimple::\ndataInternal(const ParticleAttribute& attribute,const ParticleIndex particleIndex) const\n{\n assert(attribute.attributeIndex>=0 && attribute.attributeIndex<(int)attributes.size());\n return attributeData[attribute.attributeIndex]+attributeStrides[attribute.attributeIndex]*particleIndex;\n}\n\nvoid* ParticlesSimple::\nfixedDataInternal(const FixedAttribute& attribute) const\n{\n assert(attribute.attributeIndex>=0 && attribute.attributeIndex<(int)fixedAttributes.size());\n return fixedAttributeData[attribute.attributeIndex];\n}\n\nvoid ParticlesSimple::\ndataInternalMultiple(const ParticleAttribute& attribute,const int indexCount,\n const ParticleIndex* particleIndices,const bool,char* values) const\n{\n assert(attribute.attributeIndex>=0 && attribute.attributeIndex<(int)attributes.size());\n\n char* base=attributeData[attribute.attributeIndex];\n int bytes=attributeStrides[attribute.attributeIndex];\n for(int i=0;i=0 && attribute.attributeIndex<(int)attributes.size());\n\n if(attribute.type==FLOAT || attribute.type==VECTOR) dataInternalMultiple(attribute,indexCount,particleIndices,sorted,(char*)values);\n else if(attribute.type==INT || attribute.type==INDEXEDSTR){\n char* attrrawbase=attributeData[attribute.attributeIndex];\n int* attrbase=(int*)attrrawbase;\n int count=attribute.count;\n for(int i=0;i(attrbase[particleIndices[i]*count+k]);\n }\n}\n\nint ParticlesSimple::\nregisterIndexedStr(const ParticleAttribute& attribute,const char* str)\n{\n IndexedStrTable& table=attributeIndexedStrs[attribute.attributeIndex];\n std::map::const_iterator it=table.stringToIndex.find(str);\n if(it!=table.stringToIndex.end()) return it->second;\n int newIndex=static_cast(table.strings.size());\n table.strings.push_back(str);\n table.stringToIndex[str]=newIndex;\n return newIndex;\n}\n\nint ParticlesSimple::\nregisterFixedIndexedStr(const FixedAttribute& attribute,const char* str)\n{\n IndexedStrTable& table=fixedAttributeIndexedStrs[attribute.attributeIndex];\n std::map::const_iterator it=table.stringToIndex.find(str);\n if(it!=table.stringToIndex.end()) return it->second;\n int newIndex=table.strings.size();\n table.strings.push_back(str);\n table.stringToIndex[str]=newIndex;\n return newIndex;\n}\n\nint ParticlesSimple::\nlookupIndexedStr(Partio::ParticleAttribute const &attribute, char const *str) const\n{\n const IndexedStrTable& table=attributeIndexedStrs[attribute.attributeIndex];\n std::map::const_iterator it=table.stringToIndex.find(str);\n if(it!=table.stringToIndex.end()) return it->second;\n return -1;\n}\n\nint ParticlesSimple::\nlookupFixedIndexedStr(Partio::FixedAttribute const &attribute, char const *str) const\n{\n const IndexedStrTable& table=fixedAttributeIndexedStrs[attribute.attributeIndex];\n std::map::const_iterator it=table.stringToIndex.find(str);\n if(it!=table.stringToIndex.end()) return it->second;\n return -1;\n}\n\nconst std::vector& ParticlesSimple::\nindexedStrs(const ParticleAttribute& attr) const\n{\n const IndexedStrTable& table=attributeIndexedStrs[attr.attributeIndex];\n return table.strings;\n}\n\nconst std::vector& ParticlesSimple::\nfixedIndexedStrs(const FixedAttribute& attr) const\n{\n const IndexedStrTable& table=fixedAttributeIndexedStrs[attr.attributeIndex];\n return table.strings;\n}\n\nvoid ParticlesSimple::setIndexedStr(const ParticleAttribute& attribute,int indexedStringToken,const char* str){\n IndexedStrTable& table=attributeIndexedStrs[attribute.attributeIndex];\n if(indexedStringToken >= int(table.strings.size()) || indexedStringToken < 0) return;\n table.stringToIndex.erase(table.stringToIndex.find(table.strings[indexedStringToken]));\n table.strings[indexedStringToken] = str;\n table.stringToIndex[str]=indexedStringToken;\n}\n\nvoid ParticlesSimple::setFixedIndexedStr(const FixedAttribute& attribute,int indexedStringToken,const char* str){\n IndexedStrTable& table=fixedAttributeIndexedStrs[attribute.attributeIndex];\n if(indexedStringToken >= int(table.strings.size()) || indexedStringToken < 0) return;\n table.stringToIndex.erase(table.stringToIndex.find(table.strings[indexedStringToken]));\n table.strings[indexedStringToken] = str;\n table.stringToIndex[str]=indexedStringToken;\n}\n" }, { "path": "Externals/partio/core/ParticleSimple.h", "content": "/*\nPARTIO SOFTWARE\nCopyright 2010 Disney Enterprises, Inc. All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n*/\n#include \n#include \n#include \n#include \n#include \"Mutex.h\"\n#include \"../Partio.h\"\n\nnamespace Partio{\n\ntemplate class KdTree;\n\nclass ParticlesSimple:public ParticlesDataMutable,\n public Provider\n{\nprotected:\n virtual ~ParticlesSimple();\npublic:\n using ParticlesDataMutable::iterator;\n using ParticlesData::const_iterator;\n\n virtual void release();\n\n ParticlesSimple();\n\n int numAttributes() const;\n int numFixedAttributes() const;\n int numParticles() const;\n bool attributeInfo(const char* attributeName,ParticleAttribute& attribute) const;\n bool fixedAttributeInfo(const char* attributeName,FixedAttribute& attribute) const;\n bool attributeInfo(const int attributeInfo,ParticleAttribute& attribute) const;\n bool fixedAttributeInfo(const int attributeInfo,FixedAttribute& attribute) const;\n void dataAsFloat(const ParticleAttribute& attribute,const int indexCount,\n const ParticleIndex* particleIndices,const bool sorted,float* values) const;\n int registerIndexedStr(const ParticleAttribute& attribute,const char* str);\n int registerFixedIndexedStr(const FixedAttribute& attribute,const char* str);\n void setIndexedStr(const ParticleAttribute& attribute,int indexedStringToken,const char* str);\n void setFixedIndexedStr(const FixedAttribute& attribute,int indexedStringToken,const char* str);\n int lookupIndexedStr(const ParticleAttribute& attribute,const char* str) const;\n int lookupFixedIndexedStr(const FixedAttribute& attribute,const char* str) const;\n const std::vector& indexedStrs(const ParticleAttribute& attr) const;\n const std::vector& fixedIndexedStrs(const FixedAttribute& attr) const;\n void sort();\n void findPoints(const float bboxMin[3],const float bboxMax[3],std::vector& points) const;\n float findNPoints(const float center[3],int nPoints,const float maxRadius,\n std::vector& points,std::vector& pointDistancesSquared) const;\n int findNPoints(const float center[3],int nPoints,const float maxRadius,\n ParticleIndex *points, float *pointDistancesSquared, float *finalRadius2) const;\n ParticlesDataMutable* computeClustering(const int numNeighbors,const double radiusSearch,const double radiusInside,const int connections,const double density);\n\n ParticleAttribute addAttribute(const char* attribute,ParticleAttributeType type,const int count);\n FixedAttribute addFixedAttribute(const char* attribute,ParticleAttributeType type,const int count);\n ParticleIndex addParticle();\n iterator addParticles(const int count);\n\n\n iterator setupIterator(const int index=0);\n const_iterator setupConstIterator(const int index=0) const;\n void setupIteratorNextBlock(Partio::ParticleIterator& iterator);\n void setupIteratorNextBlock(Partio::ParticleIterator& iterator) const;\n void setupAccessor(Partio::ParticleIterator& iterator,ParticleAccessor& accessor);\n void setupAccessor(Partio::ParticleIterator& iterator,ParticleAccessor& accessor) const;\nprivate:\n void* dataInternal(const ParticleAttribute& attribute,const ParticleIndex particleIndex) const;\n void* fixedDataInternal(const FixedAttribute& attribute) const;\n void dataInternalMultiple(const ParticleAttribute& attribute,const int indexCount,\n const ParticleIndex* particleIndices,const bool sorted,char* values) const;\n\nprivate:\n int particleCount;\n int allocatedCount;\n std::vector attributeData; // Inside is data of appropriate type\n std::vector attributeOffsets; // Inside is data of appropriate type\n struct IndexedStrTable{\n std::map stringToIndex; // TODO: this should be a hash table unordered_map\n std::vector strings;\n };\n std::vector attributeIndexedStrs;\n std::vector attributes;\n std::vector attributeStrides;\n std::map nameToAttribute;\n std::vector fixedAttributeData; // Inside is data of appropriate type\n std::vector fixedAttributeIndexedStrs;\n std::vector fixedAttributes;\n std::map nameToFixedAttribute;\n\n PartioMutex kdtree_mutex;\n KdTree<3>* kdtree;\n};\n\n}\n" }, { "path": "Externals/partio/core/ParticleSimpleInterleave.cpp", "content": "/*\nPARTIO SOFTWARE\nCopyright 2010 Disney Enterprises, Inc. All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n*/\n#ifdef PARTIO_WIN32\n# define NOMINMAX\n#endif\n\n#include \"ParticleSimpleInterleave.h\"\n#include \"ParticleCaching.h\"\n#include \n#include \n#include \n#include \n\n#include \"KdTree.h\"\n\n\nusing namespace Partio;\n\nParticlesSimpleInterleave::\nParticlesSimpleInterleave()\n :particleCount(0),allocatedCount(0),data(0),fixedData(0),stride(0),kdtree(0)\n{\n}\n\nParticlesSimpleInterleave::\n~ParticlesSimpleInterleave()\n{\n free(data);\n free(fixedData);\n delete kdtree;\n}\n\nvoid ParticlesSimpleInterleave::\nrelease()\n{\n freeCached(this);\n}\n\n\nint ParticlesSimpleInterleave::\nnumParticles() const\n{\n return particleCount;\n}\n\nint ParticlesSimpleInterleave::\nnumAttributes() const\n{\n return static_cast(attributes.size());\n}\n\nint ParticlesSimpleInterleave::\nnumFixedAttributes() const\n{\n return fixedAttributes.size();\n}\n\nbool ParticlesSimpleInterleave::\nattributeInfo(const int attributeIndex,ParticleAttribute& attribute) const\n{\n if(attributeIndex<0 || attributeIndex>=(int)attributes.size()) return false;\n attribute=attributes[attributeIndex];\n return true;\n}\n\nbool ParticlesSimpleInterleave::\nfixedAttributeInfo(const int attributeIndex,FixedAttribute& attribute) const\n{\n if(attributeIndex<0 || attributeIndex>=(int)fixedAttributes.size()) return false;\n attribute=fixedAttributes[attributeIndex];\n return true;\n}\n\nbool ParticlesSimpleInterleave::\nattributeInfo(const char* attributeName,ParticleAttribute& attribute) const\n{\n std::map::const_iterator it=nameToAttribute.find(attributeName);\n if(it!=nameToAttribute.end()){\n attribute=attributes[it->second];\n return true;\n }\n return false;\n}\n\nbool ParticlesSimpleInterleave::\nfixedAttributeInfo(const char* attributeName,FixedAttribute& attribute) const\n{\n std::map::const_iterator it=nameToFixedAttribute.find(attributeName);\n if(it!=nameToFixedAttribute.end()){\n attribute=fixedAttributes[it->second];\n return true;\n }\n return false;\n}\n\nvoid ParticlesSimpleInterleave::\nsort()\n{\n#if 0\n ParticleAttribute attr;\n bool foundPosition=attributeInfo(\"position\",attr);\n if(!foundPosition){\n std::cerr<<\"Partio: sort, Failed to find position in particle\"<data(attr,0); // contiguous assumption used here\n KdTree<3>* kdtree_temp=new KdTree<3>();\n kdtree_temp->setPoints(data,numParticles());\n kdtree_temp->sort();\n\n kdtree_mutex.lock();\n // TODO: this is not threadsafe!\n if(kdtree) delete kdtree;\n kdtree=kdtree_temp;\n kdtree_mutex.unlock();\n#endif\n}\n\nvoid ParticlesSimpleInterleave::\nfindPoints(const float[3],const float[3],std::vector&) const\n{\n#if 0\n if(!kdtree){\n std::cerr<<\"Partio: findPoints without first calling sort()\"< box(bboxMin);box.grow(bboxMax);\n\n int startIndex=points.size();\n kdtree->findPoints(points,box);\n // remap points found in findPoints to original index spac\n for(unsigned int i=startIndex;iid(points[i]);\n#endif\n}\n\nfloat ParticlesSimpleInterleave::\nfindNPoints(const float[3],const int,const float,std::vector&,\n std::vector&) const\n{\n#if 0\n if(!kdtree){\n std::cerr<<\"Partio: findNPoints without first calling sort()\"<findNPoints(points,pointDistancesSquared,center,nPoints,maxRadius);\n // remap all points since findNPoints clears array\n for(unsigned int i=0;iid(points[i]);\n return maxDistance;\n#endif\n return 0;\n}\n\nint ParticlesSimpleInterleave::\nfindNPoints(const float[3], int, const float, ParticleIndex *,\n float *, float *) const\n{\n // TODO: I guess they don't support this lookup here\n return 0;\n}\n\n\nParticleAttribute ParticlesSimpleInterleave::\naddAttribute(const char* attribute,ParticleAttributeType type,const int count)\n{\n\t//std::cerr<< \"AddAttribute interleave\" << std::endl;\n if(nameToAttribute.find(attribute) != nameToAttribute.end()){\n std::cerr<<\"Partio: addAttribute failed because attr '\"<(attributes.size()); // all arrays separate so we don't use this here!\n attr.count=count;\n attributes.push_back(attr);\n nameToAttribute[attribute]=static_cast(attributes.size()-1);\n\n // repackage data for new attribute\n int oldStride=stride;\n int newStride=stride+TypeSize(type)*count;\n char* newData=(char*)malloc((size_t)allocatedCount*(size_t)newStride);\n if(data){\n char* ptrNew=newData;\n char* ptrOld=data;\n for(int i=0;iallocatedCount){\n while(allocatedCount& iterator)\n{\n iterator=end();\n}\n\nvoid ParticlesSimpleInterleave::\nsetupIteratorNextBlock(Partio::ParticleIterator& iterator) const\n{\n iterator=ParticlesData::end();\n}\n\nvoid ParticlesSimpleInterleave::\nsetupAccessor(Partio::ParticleIterator&,ParticleAccessor& accessor)\n{\n accessor.stride=stride;\n accessor.basePointer=data+attributeOffsets[accessor.attributeIndex];\n}\n\nvoid ParticlesSimpleInterleave::\nsetupAccessor(Partio::ParticleIterator&,ParticleAccessor& accessor) const\n{\n accessor.stride=stride;\n accessor.basePointer=data+attributeOffsets[accessor.attributeIndex];\n}\n\n\nvoid* ParticlesSimpleInterleave::\ndataInternal(const ParticleAttribute& attribute,const ParticleIndex particleIndex) const\n{\n return data+particleIndex*stride+attributeOffsets[attribute.attributeIndex];\n}\n\nvoid* ParticlesSimpleInterleave::\nfixedDataInternal(const FixedAttribute& attribute) const\n{\n return data+allocatedCount*stride+fixedAttributeOffsets[attribute.attributeIndex];\n}\n\nvoid ParticlesSimpleInterleave::\ndataInternalMultiple(const ParticleAttribute&,const int,const ParticleIndex*,const bool,char*) const\n{\n#if 0\n assert(attribute.attributeIndex>=0 && attribute.attributeIndex<(int)attributes.size());\n\n char* base=attributeData[attribute.attributeIndex];\n int bytes=attributeStrides[attribute.attributeIndex];\n for(int i=0;i=0 && attribute.attributeIndex<(int)attributes.size());\n\n if(attribute.type==FLOAT || attribute.type==VECTOR) dataInternalMultiple(attribute,indexCount,particleIndices,sorted,(char*)values);\n else if(attribute.type==INT){\n char* attrrawbase=attributeData[attribute.attributeIndex];\n int* attrbase=(int*)attrrawbase;\n int count=attribute.count;\n for(int i=0;i::const_iterator it=table.stringToIndex.find(str);\n if(it!=table.stringToIndex.end()) return it->second;\n int newIndex=static_cast(table.strings.size());\n table.strings.push_back(str);\n table.stringToIndex[str]=newIndex;\n return newIndex;\n}\n\nint ParticlesSimpleInterleave::\nregisterFixedIndexedStr(const FixedAttribute& attribute,const char* str)\n{\n IndexedStrTable& table=fixedAttributeIndexedStrs[attribute.attributeIndex];\n std::map::const_iterator it=table.stringToIndex.find(str);\n if(it!=table.stringToIndex.end()) return it->second;\n int newIndex=table.strings.size();\n table.strings.push_back(str);\n table.stringToIndex[str]=newIndex;\n return newIndex;\n}\n\nint ParticlesSimpleInterleave::\nlookupIndexedStr(Partio::ParticleAttribute const &attribute, char const *str) const\n{\n const IndexedStrTable& table=attributeIndexedStrs[attribute.attributeIndex];\n std::map::const_iterator it=table.stringToIndex.find(str);\n if(it!=table.stringToIndex.end()) return it->second;\n return -1;\n}\n\nint ParticlesSimpleInterleave::\nlookupFixedIndexedStr(Partio::FixedAttribute const &attribute, char const *str) const\n{\n const IndexedStrTable& table=fixedAttributeIndexedStrs[attribute.attributeIndex];\n std::map::const_iterator it=table.stringToIndex.find(str);\n if(it!=table.stringToIndex.end()) return it->second;\n return -1;\n}\n\nconst std::vector& ParticlesSimpleInterleave::\nindexedStrs(const ParticleAttribute& attr) const\n{\n const IndexedStrTable& table=attributeIndexedStrs[attr.attributeIndex];\n return table.strings;\n}\n\nconst std::vector& ParticlesSimpleInterleave::\nfixedIndexedStrs(const FixedAttribute& attr) const\n{\n const IndexedStrTable& table=fixedAttributeIndexedStrs[attr.attributeIndex];\n return table.strings;\n}\n\n\nvoid ParticlesSimpleInterleave::setIndexedStr(const ParticleAttribute& attribute,int indexedStringToken,const char* str){\n IndexedStrTable& table=attributeIndexedStrs[attribute.attributeIndex];\n if(indexedStringToken >= int(table.strings.size()) || indexedStringToken < 0) return;\n table.stringToIndex.erase(table.stringToIndex.find(table.strings[indexedStringToken]));\n table.strings[indexedStringToken] = str;\n table.stringToIndex[str]=indexedStringToken;\n}\n\nvoid ParticlesSimpleInterleave::setFixedIndexedStr(const FixedAttribute& attribute,int indexedStringToken,const char* str){\n IndexedStrTable& table=fixedAttributeIndexedStrs[attribute.attributeIndex];\n if(indexedStringToken >= int(table.strings.size()) || indexedStringToken < 0) return;\n table.stringToIndex.erase(table.stringToIndex.find(table.strings[indexedStringToken]));\n table.strings[indexedStringToken] = str;\n table.stringToIndex[str]=indexedStringToken;\n}\n" }, { "path": "Externals/partio/core/ParticleSimpleInterleave.h", "content": "/*\nPARTIO SOFTWARE\nCopyright 2010 Disney Enterprises, Inc. All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n*/\n#ifndef _ParticleSimpleInterleave_h_\n#define _ParticleSimpleInterleave_h_\n\n#include \n#include \n#include \n#include \"Mutex.h\"\n#include \"../Partio.h\"\n\nnamespace Partio{\n\ntemplate class KdTree;\n\nclass ParticlesSimpleInterleave:public ParticlesDataMutable,\n public Provider\n{\nprotected:\n virtual ~ParticlesSimpleInterleave();\npublic:\n using ParticlesDataMutable::iterator;\n using ParticlesData::const_iterator;\n\n virtual void release();\n\n ParticlesSimpleInterleave();\n\n int numAttributes() const;\n int numFixedAttributes() const;\n int numParticles() const;\n bool attributeInfo(const char* attributeName,ParticleAttribute& attribute) const;\n bool fixedAttributeInfo(const char* attributeName,FixedAttribute& attribute) const;\n bool attributeInfo(const int attributeInfo,ParticleAttribute& attribute) const;\n bool fixedAttributeInfo(const int attributeInfo,FixedAttribute& attribute) const;\n\n virtual void dataAsFloat(const ParticleAttribute& attribute,const int indexCount,\n const ParticleIndex* particleIndices,const bool sorted,float* values) const;\n int registerIndexedStr(const ParticleAttribute& attribute,const char* str);\n int registerFixedIndexedStr(const FixedAttribute& attribute,const char* str);\n void setIndexedStr(const ParticleAttribute& attribute,int indexedStringToken,const char* str);\n void setFixedIndexedStr(const FixedAttribute& attribute,int indexedStringToken,const char* str);\n int lookupIndexedStr(const ParticleAttribute& attribute,const char* str) const;\n int lookupFixedIndexedStr(const FixedAttribute& attribute,const char* str) const;\n const std::vector& indexedStrs(const ParticleAttribute& attr) const;\n const std::vector& fixedIndexedStrs(const FixedAttribute& attr) const;\n\n void sort();\n void findPoints(const float bboxMin[3],const float bboxMax[3],std::vector& points) const;\n float findNPoints(const float center[3],int nPoints,const float maxRadius,\n std::vector& points,std::vector& pointDistancesSquared) const;\n int findNPoints(const float center[3],int nPoints,const float maxRadius,\n ParticleIndex *points, float *pointDistancesSquared, float *finalRadius2) const;\n ParticlesDataMutable* computeClustering(const int numNeighbors,const double radiusSearch,const double radiusInside,const int connections,const double density)\n { assert(false); return nullptr; }\n\n ParticleAttribute addAttribute(const char* attribute,ParticleAttributeType type,const int count);\n FixedAttribute addFixedAttribute(const char* attribute,ParticleAttributeType type,const int count);\n ParticleIndex addParticle();\n iterator addParticles(const int count);\n\n\n iterator setupIterator(const int index=0);\n const_iterator setupConstIterator(const int index=0) const;\n void setupIteratorNextBlock(Partio::ParticleIterator& iterator);\n void setupIteratorNextBlock(Partio::ParticleIterator& iterator) const;\n void setupAccessor(Partio::ParticleIterator& iterator,ParticleAccessor& accessor);\n void setupAccessor(Partio::ParticleIterator& iterator,ParticleAccessor& accessor) const;\nprivate:\n void* dataInternal(const ParticleAttribute& attribute,const ParticleIndex particleIndex) const;\n void* fixedDataInternal(const FixedAttribute& attribute) const;\n void dataInternalMultiple(const ParticleAttribute& attribute,const int indexCount,\n const ParticleIndex* particleIndices,const bool sorted,char* values) const;\n\nprivate:\n int particleCount;\n int allocatedCount;\n char* data;\n char* fixedData;\n int stride;\n\tstruct IndexedStrTable{\n std::map stringToIndex; // TODO: this should be a hash table unordered_map\n std::vector strings;\n };\n\tstd::vector attributeIndexedStrs;\n std::vector attributeOffsets; // Inside is data of appropriate type\n std::vector attributes;\n std::map nameToAttribute;\n std::vector fixedAttributeIndexedStrs;\n std::vector fixedAttributeOffsets; // Inside is data of appropriate type\n std::vector fixedAttributes;\n std::map nameToFixedAttribute;\n\n PartioMutex kdtree_mutex;\n KdTree<3>* kdtree;\n};\n\n}\n#endif\n" }, { "path": "Externals/partio/io/BGEO.cpp", "content": "/*\nPARTIO SOFTWARE\nCopyright 2010 Disney Enterprises, Inc. All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n*/\n\n#include \"../Partio.h\"\n#include \"PartioEndian.h\"\n#include \"../core/ParticleHeaders.h\"\n#include \"ZIP.h\"\n\n#include \n#include \n#include \n#include \n#include \n\n#include \n\nnamespace Partio\n{\n\nusing namespace std;\n\nvoid writeHoudiniStr(ostream& ostream,const string& s)\n{\n write(ostream,(short)s.size());\n ostream.write(s.c_str(),s.size());\n}\n\ntemplate\nstruct Helper\n{\n T addAttribute(ParticlesDataMutable* simple, const char* name, ParticleAttributeType type, int size);\n int registerIndexedStr(const T& attribute,const char* str);\n};\ntemplate<>\nstruct Helper\n{\n ParticleAttribute addAttribute(ParticlesDataMutable* simple, const char* name, ParticleAttributeType type, int size) {return simple->addAttribute(name,type,size);}\n int registerIndexedStr(ParticlesDataMutable* simple, const ParticleAttribute& attribute,const char* str) {return simple->registerIndexedStr(attribute,str);}\n};\ntemplate<>\nstruct Helper\n{\n FixedAttribute addAttribute(ParticlesDataMutable* simple, const char* name, ParticleAttributeType type, int size) {return simple->addFixedAttribute(name,type,size);}\n int registerIndexedStr(ParticlesDataMutable* simple, const FixedAttribute& attribute,const char* str) {return simple->registerFixedIndexedStr(attribute,str);}\n};\n\nclass DummyAttribute {};\ntemplate<>\nstruct Helper\n{\n DummyAttribute addAttribute(ParticlesDataMutable* simple, const char* name, ParticleAttributeType type, int size) { return DummyAttribute(); }\n int registerIndexedStr(ParticlesDataMutable* simple, const DummyAttribute& attribute,const char* str) { return 0; }\n};\nstruct DummyAccessor{\n template\n DummyAccessor(const T& /*attr*/){}\n};\n\ntemplate\nbool getAttributes(int& particleSize, vector& attrOffsets, vector& attrHandles, vector& accessors, int nAttrib, istream* input, ParticlesDataMutable* simple, bool headersOnly, std::ostream* errorStream)\n{\n Helper helper;\n for(int i=0;i(*input,nameLength);\n char* name=new char[nameLength+1];\n input->read(name,nameLength);name[nameLength]=0;\n unsigned short size;\n int houdiniType;\n read(*input,size,houdiniType);\n if(houdiniType==0 || houdiniType==1 || houdiniType==5){\n // read default values. don't do anything with them\n for(int i=0;iread((char*)&defaultValue,sizeof(int));\n }\n ParticleAttributeType type=NONE;\n if(houdiniType==0) type=FLOAT;\n else if(houdiniType==1) type=INT;\n else if(houdiniType==5) type=VECTOR;\n attrHandles.push_back(helper.addAttribute(simple,name,type,size));\n accessors.push_back(TAccessor(attrHandles.back()));\n attrOffsets.push_back(particleSize);\n particleSize+=size;\n }else if(houdiniType==4){\n TAttribute attribute=helper.addAttribute(simple,name,INDEXEDSTR,size);\n attrHandles.push_back(attribute);\n accessors.push_back(TAccessor(attrHandles.back()));\n attrOffsets.push_back(particleSize);\n int numIndices=0;\n read(*input,numIndices);\n for(int ii=0;ii(*input,indexNameLength);\n char* indexName=new char[indexNameLength+1];;\n input->read(indexName,indexNameLength);\n indexName[indexNameLength]=0;\n if (!headersOnly) {\n int id=helper.registerIndexedStr(simple,attribute,indexName);\n if(id != ii){\n if(errorStream) *errorStream <<\"Partio: error on read, expected registerIndexStr to return index \"<release();\n return 0;\n }else{\n if(errorStream) *errorStream <<\"Partio: unknown attribute \"<release();\n return 0;\n }\n delete[] name;\n }\n\n return true;\n}\n\n// read buffer, seekg doesn't work with gzip\nvoid skip(istream *input, size_t numChars)\n{\n static const size_t bufferSize = 4096;\n static char buffer[bufferSize];\n while (numChars>0) {\n int toRead=std::min(numChars,bufferSize);\n input->read(buffer,toRead);\n numChars-=toRead;\n }\n}\n\n// ignore primitive attributes, only know about Particle Systems currently\nbool skipPrimitives(int nPoints, int nPrims, int nPrimAttrib, istream* input,std::ostream* errorStream)\n{\n int particleSize=0;\n vector primAttrOffsets; // offsets in # of 32 bit offsets\n vector primAttrHandles;\n vector primAccessors;\n getAttributes(particleSize, primAttrOffsets, primAttrHandles, primAccessors, nPrimAttrib, input, 0, true, errorStream);\n\n for(int i=0;i(*input,primType);\n if(primType==0x00008000) {\n int size;\n read(*input,size);\n if(nPoints>=(int)1<<16)\n skip(input,size*sizeof(int));\n else\n skip(input,size*sizeof(unsigned short));\n skip(input,particleSize*sizeof(int));\n } else {\n if(errorStream) *errorStream << \"Partio: Unrecognized Primitive Type: 0x\" << std::hex << primType << \" - Cannot process detail attributes\" << std::endl;\n return false;\n }\n }\n return true;\n}\n\nParticlesDataMutable* readBGEO(const char* filename,const bool headersOnly,std::ostream* errorStream)\n{\n unique_ptr input(Gzip_In(filename,ios::in|ios::binary));\n if(!*input){\n if(errorStream) *errorStream<<\"Partio: Unable to open file \"<(*input,magic[0],magic[1],magic[2],magic[3]);\n read(*input,versionChar,version,nPoints,nPrims,nPointGroups);\n read(*input,nPrimGroups,nPointAttrib,nVertexAttrib,nPrimAttrib,nAttrib);\n\n\n // Check header magic and version\n const char bgeo_magic[5]={'B','g','e','o',0};\n if(strcmp(magic,bgeo_magic)){\n const char new_bgeo_magic[5]={0x7f,0x4e,0x53,0x4a,0};\n if(!strcmp(magic,new_bgeo_magic)){\n if(errorStream) *errorStream<<\"Partio: Attempting to read new BGEO format, we only support old BGEO format. Try writing .bhclassic from Houdini.\"<addParticles(nPoints);\n\n\n // Read attribute definitions\n int particleSize=4; // Size in # of 32 bit primitives \n vector attrOffsets; // offsets in # of 32 bit offsets\n vector attrHandles;\n vector accessors;\n attrOffsets.push_back(0); // pull values from byte offset\n attrHandles.push_back(simple->addAttribute(\"position\",VECTOR,3)); // we always have one\n accessors.push_back(ParticleAccessor(attrHandles[0]));\n getAttributes(particleSize, attrOffsets, attrHandles, accessors, nPointAttrib, input.get(), simple, headersOnly, errorStream);\n\n if(headersOnly) {\n skip(input.get(),nPoints*particleSize*sizeof(int));\n } else {\n // Read the points\n int *buffer=new int[particleSize];\n\n // make iterator and register accessors\n ParticlesDataMutable::iterator iterator=simple->begin();\n for(size_t i=0;iend();iterator!=end;++iterator){\n input->read((char*)buffer,particleSize*sizeof(int));\n for(unsigned int attrIndex=0;attrIndex(iterator);\n for(int k=0;k fixedAttrOffsets; // offsets in # of 32 bit offsets\n vector fixedAttrHandles;\n vector fixedAccessors;\n getAttributes(particleSize, fixedAttrOffsets, fixedAttrHandles, fixedAccessors, nAttrib, input.get(), simple, headersOnly, errorStream);\n\n if (headersOnly) return simple;\n\n // Read the points\n int *fixedBuffer=new int[particleSize];\n input->read((char*)fixedBuffer,particleSize*sizeof(int));\n for(unsigned int attrIndex=0;attrIndexfixedDataWrite(fixedAttrHandles[attrIndex])[k]=fixedBuffer[fixedAttrOffsets[attrIndex]+k];\n }\n }\n delete [] fixedBuffer;\n\n // return the populated simpleParticle\n return simple;\n}\n\nbool writeBGEO(const char* filename,const ParticlesData& p,const bool compressed,std::ostream* errorStream)\n{\n unique_ptr output(\n compressed ? \n Gzip_Out(filename,ios::out|ios::binary)\n :new ofstream(filename,ios::out|ios::binary));\n\n if(!*output){\n if(errorStream) *errorStream <<\"Partio Unable to open file \"<(*output,magic,versionChar,version,nPoints,nPrims,nPointGroups);\n write(*output,nPrimGroups,nPointAttrib,nVertexAttrib,nPrimAttrib,nAttrib);\n\n vector handles;\n vector accessors;\n vector attrOffsets;\n bool foundPosition=false;\n int particleSize=4;\n for(int i=0;i(attr.count);\n const std::vector& indexTable=p.indexedStrs(attr);\n int numIndexes=static_cast(indexTable.size());\n write(*output,size,houdiniType,numIndexes);\n for(int i=0;i(attr.count);\n write(*output,size,houdiniType);\n for(int i=0;i(*output,defaultValue);\n }\n }\n attrOffsets.push_back(particleSize);\n particleSize+=attr.count;\n }\n handles.push_back(attr);\n accessors.push_back(ParticleAccessor(handles.back()));\n }\n if(!foundPosition){\n if(errorStream) *errorStream <<\"Partio: didn't find attr 'position' while trying to write GEO\"<(iterator);\n for(int k=0;kwrite((char*)buffer,particleSize*sizeof(int));\n }\n delete [] buffer;\n\n vector fixedHandles;\n vector fixedAttrOffsets;\n particleSize=0;\n for(int i=0;i& indexTable=p.fixedIndexedStrs(attr);\n int numIndexes=indexTable.size();\n write(*output,size,houdiniType,numIndexes);\n for(int ii=0;ii(*output,size,houdiniType);\n for(int i=0;i(*output,defaultValue);\n }\n }\n fixedAttrOffsets.push_back(particleSize);\n particleSize+=attr.count;\n\n fixedHandles.push_back(attr);\n }\n\n int *fixedBuffer=new int[particleSize];\n\n for(unsigned int attrIndex=0;attrIndex(fixedHandles[attrIndex])[k];\n BIGEND::swap(fixedBuffer[fixedAttrOffsets[attrIndex]+k]);\n }\n }\n output->write((char*)fixedBuffer,particleSize*sizeof(int));\n\n delete [] fixedBuffer;\n\n // Write extra\n write(*output,(char)0x00);\n#ifdef _MSC_VER \n\t#pragma warning (push) \n\t#pragma warning (disable : 4310 ) // suppress the warning for 0xff being truncated to 0x7f (max value of a signed char)\n#endif \n write(*output,(char)0xff);\n#ifdef _MSC_VER \n\t#pragma warning (pop) \n#endif \n\n // success\n return true;\n}\n\n}\n" }, { "path": "Externals/partio/io/BIN.cpp", "content": "/*\nPARTIO SOFTWARE\nCopyright (c) 2011 Disney Enterprises, Inc. and Contributors, All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n\nFormat Contributed by github user: Jinkuen\nSome code for this format was helped along by referring to an implementation by Digital Cinema Arts THANKS!\nModifications from: github user: redpawfx (redpawFX@gmail.com) and Luma Pictures 2011\n\n*/\n\n#include \"../Partio.h\"\n#include \"../core/ParticleHeaders.h\"\n#include \"PartioEndian.h\"\n#include \"ZIP.h\"\n\n#include \n#include \n#include \n#include \n\nnamespace Partio{\n\nusing namespace std;\n\nstatic const long BIN_MAGIC = 0xFABADA;\n\ntypedef struct{\n int verificationCode;\n char fluidName[250] ;\n short version;\n float scaleScene;\n int fluidType;\n float elapsedSimulationTime;\n int frameNumber;\n int framePerSecond;\n int numParticles;\n float radius;\n float pressure[3];\n float speed[3];\n float temperature[3];\n float emitterPosition[3];\n float emitterRotation[3];\n float emitterScale[3];\n} BIN_HEADER;\n\ntypedef struct{\n int verificationCode;\n char fluidName[250] ;\n short version;\n float scaleScene;\n int fluidType;\n float elapsedSimulationTime;\n int frameNumber;\n int framePerSecond;\n int numParticles;\n float radius;\n float pressure[3];\n float speed[3];\n float temperature[3];\n} BIN_HEADERV6;\n\n\nParticlesDataMutable* readBIN(const char* filename, const bool headersOnly,std::ostream* errorStream){\n\n unique_ptr input(new ifstream(filename,ios::in|ios::binary));\n\n if(!*input){\n if(errorStream) *errorStream << \"Partio: Unable to open file \" << filename << endl;\n return 0;\n }\n\n BIN_HEADER header;\n input->read((char*)&header, sizeof(BIN_HEADERV6));\n\n // According to the NextLimit bin_particles_file_format.pdf file\n if (header.version >= 7)\n {\n input->read((char*)&header.emitterPosition, sizeof(header.emitterPosition));\n input->read((char*)&header.emitterRotation, sizeof(header.emitterRotation));\n input->read((char*)&header.emitterScale, sizeof(header.emitterScale));\n }\n\n // After version 13, we don't know what to do\n if(header.version > 13){\n cerr << \"Partio: Unknown .bin version : \" << header.version << endl;\n return 0;\n }\n\n if(BIN_MAGIC != header.verificationCode){\n if(errorStream) *errorStream<< \"Partio: Magic number '\" << hex<< header.verificationCode << \"' of '\" << filename << \"' doesn't match BIN magic '\" << BIN_MAGIC << \"'\" << endl;\n return 0;\n }\n\n\n ParticlesDataMutable* simple = headersOnly ? new ParticleHeaders: create();\n simple->addParticles(header.numParticles);\n\n ParticleAttribute posAttr;\n posAttr = simple->addAttribute(\"position\", VECTOR, 3);\n ParticleAttribute veloAttr;\n veloAttr = simple->addAttribute(\"velocity\", VECTOR, 3);\n ParticleAttribute forceAttr;\n forceAttr = simple->addAttribute(\"force\", VECTOR, 3);\n ParticleAttribute vortAttr;\n if (header.version >= 9)\n vortAttr = simple->addAttribute(\"vorticity\", VECTOR, 3);\n ParticleAttribute normAttr;\n if (header.version >= 3)\n normAttr = simple->addAttribute(\"normal\", VECTOR, 3);\n ParticleAttribute neighborsAttr;\n if (header.version >= 4)\n neighborsAttr = simple->addAttribute(\"neighbors\", INT, 1);\n ParticleAttribute uvwAttr;\n if (header.version >= 5)\n uvwAttr = simple->addAttribute(\"uvw\", VECTOR, 3);\n ParticleAttribute ageAttr;\n ageAttr = simple->addAttribute(\"age\", FLOAT, 1);\n ParticleAttribute isoTimeAttr;\n isoTimeAttr = simple->addAttribute(\"isolationTime\", FLOAT, 1);\n ParticleAttribute viscosityAttr;\n viscosityAttr = simple->addAttribute(\"viscosity\", FLOAT, 1);\n ParticleAttribute densityAttr;\n densityAttr = simple->addAttribute(\"density\", FLOAT, 1);\n ParticleAttribute pressureAttr;\n pressureAttr = simple->addAttribute(\"pressure\", FLOAT, 1);\n ParticleAttribute massAttr;\n massAttr = simple->addAttribute(\"mass\", FLOAT, 1);\n ParticleAttribute tempAttr;\n tempAttr = simple->addAttribute(\"temperature\", FLOAT, 1);\n ParticleAttribute pidAttr;\n pidAttr = simple->addAttribute(\"id\", INT, 1);\n\n if (!headersOnly)\n {\n for(int partIndex = 0; partIndex < simple->numParticles(); partIndex++)\n {\n\n float position[3] = {0.0,0.0,0.0};\n float velocity[3] = {0.0,0.0,0.0};\n float force[3] = {0.0,0.0,0.0};\n float vorticity[3] = {0.0,0.0,0.0};\n float normal[3] = {0.0,0.0,0.0};\n int neighbors = 0;\n float uvw[3] = {0.0,0.0,0.0};\n short infoBits = 7;\n float age = 0.0;\n float isolationTime = 1.0;\n float viscosity = 1.0;\n float density = 1.0;\n float pressure = 1.0;\n float mass = 1.0;\n float temperature = 1.0;\n int pid = 0;\n\n input->read ((char *) &position[0], sizeof(float));\n simple->dataWrite(posAttr, partIndex)[0] = (float)position[0];\n input->read ((char *) &position[1], sizeof(float));\n simple->dataWrite(posAttr, partIndex)[1] = (float)position[1];\n input->read ((char *) &position[2], sizeof(float));\n simple->dataWrite(posAttr, partIndex)[2] = (float)position[2];\n\n\n input->read ((char *) &velocity[0], sizeof(float));\n simple->dataWrite(veloAttr, partIndex)[0] = (float)velocity[0];\n input->read ((char *) &velocity[1], sizeof(float));\n simple->dataWrite(veloAttr, partIndex)[1] = (float)velocity[1];\n input->read ((char *) &velocity[2], sizeof(float));\n simple->dataWrite(veloAttr, partIndex)[2] = (float)velocity[2];\n\n input->read ((char *) &force[0], sizeof(float));\n simple->dataWrite(forceAttr, partIndex)[0] = (float)force[0];\n input->read ((char *) &force[1], sizeof(float));\n simple->dataWrite(forceAttr, partIndex)[1] = (float)force[1];\n input->read ((char *) &force[2], sizeof(float));\n simple->dataWrite(forceAttr, partIndex)[2] = (float)force[2];\n\n if (header.version >= 9)\n {\n input->read ((char *) &vorticity[0], sizeof(float));\n simple->dataWrite(vortAttr, partIndex)[0] = (float)vorticity[0];\n input->read ((char *) &vorticity[1], sizeof(float));\n simple->dataWrite(vortAttr, partIndex)[1] = (float)vorticity[1];\n input->read ((char *) &vorticity[2], sizeof(float));\n simple->dataWrite(vortAttr, partIndex)[2] = (float)vorticity[2];\n }\n\n if (header.version >= 3)\n {\n input->read ((char *) &normal[0], sizeof(float));\n simple->dataWrite(normAttr, partIndex)[0] = (float)normal[0];\n input->read ((char *) &normal[1], sizeof(float));\n simple->dataWrite(normAttr, partIndex)[1] = (float)normal[1];\n input->read ((char *) &normal[2], sizeof(float));\n simple->dataWrite(normAttr, partIndex)[2] = (float)normal[2];\n }\n\n if (header.version >= 4)\n {\n input->read ((char *) &neighbors, sizeof (int));\n simple->dataWrite(neighborsAttr, partIndex)[0] = (int)neighbors;\n }\n\n if (header.version >= 5)\n {\n input->read ((char *) &uvw[0], sizeof(float));\n simple->dataWrite(uvwAttr, partIndex)[0] = (float)uvw[0];\n input->read ((char *) &uvw[1], sizeof(float));\n simple->dataWrite(uvwAttr, partIndex)[1] = (float)uvw[1];\n input->read ((char *) &uvw[2], sizeof(float));\n simple->dataWrite(uvwAttr, partIndex)[2] = (float)uvw[2];\n\n input->read ((char *) &infoBits, sizeof(infoBits));\n }\n\n // don't do anything with this..\n input->read ((char *) &age, sizeof(age));\n simple->dataWrite(ageAttr, partIndex)[0] = (float)age;\n input->read ((char *) &isolationTime, sizeof(isolationTime));\n simple->dataWrite(isoTimeAttr, partIndex)[0] = (float)isolationTime;\n input->read ((char *) &viscosity, sizeof(viscosity));\n simple->dataWrite(viscosityAttr, partIndex)[0] = (float)viscosity;\n input->read ((char *) &density, sizeof(density));\n simple->dataWrite(densityAttr, partIndex)[0] = (float)density;\n input->read ((char *) &pressure, sizeof(pressure));\n simple->dataWrite(pressureAttr, partIndex)[0] = (float)pressure;\n input->read ((char *) &mass, sizeof(mass));\n simple->dataWrite(massAttr, partIndex)[0] = (float)mass;\n input->read ((char *) &temperature, sizeof(temperature));\n simple->dataWrite(tempAttr, partIndex)[0] = (float)temperature;\n\n // pid\n if (header.version < 12)\n input->read ((char *) &pid, sizeof(pid));\n else\n {\n // Warning, cast the id on 32 bits here\n uint64_t pid64;\n input->read ((char*) &pid64, sizeof(pid64));\n pid = (int)pid64;\n }\n simple->dataWrite(pidAttr, partIndex)[0] = (int)pid;\n }\n }\n\n return simple;\n}\n\nbool writeBIN(const char* filename,const ParticlesData& p,const bool /*compressed*/,std::ostream* errorStream)\n{\n\n unique_ptr output(\n new ofstream(filename,ios::out|ios::binary));\n\n if (!*output) {\n if(errorStream) *errorStream<<\"Partio Unable to open file \"<write ((const char *) &header.verificationCode, sizeof (int));\n output->write ((const char *) &header.fluidName, 250);\n output->write ((const char *) &header.version, sizeof (short int));\n output->write ((const char *) &header.scaleScene, sizeof (float));\n output->write ((const char *) &header.fluidType, sizeof (int));\n output->write ((const char *) &header.elapsedSimulationTime, sizeof (float));\n output->write ((const char *) &header.frameNumber, sizeof (int));\n output->write ((const char *) &header.framePerSecond, sizeof (int));\n output->write ((const char *) &header.numParticles, sizeof (int));\n output->write ((const char *) &header.radius, sizeof (float));\n\n for(int i=0; i <=2; i++)\n\t\toutput->write ((const char *) &header.pressure[i], sizeof(float));\n for(int i=0; i<= 2; i++)\n output->write ((const char *) &header.speed[i], sizeof(float));\n for(int i=0; i<= 2; i++)\n output->write ((const char *) &header.temperature[i], sizeof(float));\n\n for(int i=0; i<= 2; i++)\n output->write ((const char *) &header.emitterPosition[i], sizeof(float));\n for(int i=0; i <= 2; i++)\n output->write ((const char *) &header.emitterRotation[i], sizeof(float));\n for(int i=0; i <= 2; i++)\n output->write ((const char *) &header.emitterScale[i], sizeof(float));\n\n for (int particles = 0; particles < p.numParticles(); particles++)\n {\n // set defaults for stuff that is not exported...\n float position[3] = {0.0,0.0,0.0};\n float velocity[3] = {0.0,0.0,0.0};\n float force[3] = {0.0,0.0,0.0};\n float vorticity[3] = {0.0,0.0,0.0};\n float normal[3] = {0.0,0.0,0.0};\n int neighbors = 0;\n float uvw[3] = {0.0,0.0,0.0};\n short infoBits = 7;\n float age = 0.0;\n float isolationTime = 1.0;\n float viscosity = 1.0;\n float density = 1.0;\n float pressure = 1.0;\n float mass = 1.0;\n float temperature = 1.0;\n int pid = particles;\n\n // now run thru the exported attrs and replace values for things that we do have\n\n for(int attrIndex = 0; attrIndex < p.numAttributes(); attrIndex++)\n {\n ParticleAttribute attr;\n p.attributeInfo(attrIndex,attr);\n\n //cout << attr.name << endl;\n if (attr.name == \"position\")\n {\n const float* data = p.data(attr, particles);\n position[0] = data[0];\n position[1] = data[1];\n position[2] = data[2];\n }\n\n else if (attr.name == \"velocity\")\n {\n const float* data = p.data(attr, particles);\n velocity[0] = data[0];\n velocity[1] = data[1];\n velocity[2] = data[2];\n }\n else if (attr.name == \"force\")\n {\n const float* data = p.data(attr, particles);\n force[0] = data[0];\n force[1] = data[1];\n force[2] = data[2];\n }\n else if (attr.name == \"vorticity\")\n {\n const float* data = p.data(attr, particles);\n vorticity[0] = data[0];\n vorticity[1] = data[1];\n vorticity[2] = data[2];\n }\n else if (attr.name == \"normal\")\n {\n const float* data = p.data(attr, particles);\n normal[0] = data[0];\n normal[1] = data[1];\n normal[2] = data[2];\n }\n else if (attr.name == \"neighbors\")\n {\n const int* data = p.data(attr, particles);\n neighbors= data[0];\n }\n else if (attr.name == \"uvw\")\n {\n const float* data = p.data(attr, particles);\n uvw[0] = data[0];\n uvw[1] = data[1];\n uvw[2] = data[2];\n }\n else if (attr.name == \"age\")\n {\n const float* data = p.data(attr, particles);\n age= data[0];\n }\n else if (attr.name == \"isolationTime\")\n {\n const float* data = p.data(attr, particles);\n isolationTime= data[0];\n }\n else if (attr.name == \"viscosity\")\n {\n const float* data = p.data(attr, particles);\n viscosity= data[0];\n }\n else if (attr.name == \"density\")\n {\n const float* data = p.data(attr, particles);\n density= data[0];\n }\n else if (attr.name == \"pressure\")\n {\n const float* data = p.data(attr, particles);\n pressure= data[0];\n }\n else if (attr.name == \"mass\")\n {\n const float* data = p.data(attr, particles);\n mass= data[0];\n }\n else if (attr.name == \"temperature\")\n {\n const float* data = p.data(attr, particles);\n temperature= data[0];\n }\n else if (attr.name == \"id\")\n {\n const int* data = p.data(attr, particles);\n pid= data[0];\n }\n\n else\n {\n cout << \"Attribute found that we don't support yet\" << endl;\n }\n }\n\n output->write ((const char *) &position[0], sizeof (float));\n output->write ((const char *) &position[1], sizeof (float));\n output->write ((const char *) &position[2], sizeof (float));\n\n output->write ((const char *) &velocity[0], sizeof (float));\n output->write ((const char *) &velocity[1], sizeof (float));\n output->write ((const char *) &velocity[2], sizeof (float));\n\n output->write ((const char *) &force[0], sizeof (float));\n output->write ((const char *) &force[1], sizeof (float));\n output->write ((const char *) &force[2], sizeof (float));\n\n output->write ((const char *) &vorticity[0], sizeof (float));\n output->write ((const char *) &vorticity[1], sizeof (float));\n output->write ((const char *) &vorticity[2], sizeof (float));\n\n output->write ((const char *) &normal[0], sizeof (float));\n output->write ((const char *) &normal[1], sizeof (float));\n output->write ((const char *) &normal[2], sizeof (float));\n\n output->write ((const char *) &neighbors, sizeof (neighbors));\n\n output->write ((const char *) &uvw[0], sizeof (float));\n output->write ((const char *) &uvw[1], sizeof (float));\n output->write ((const char *) &uvw[2], sizeof (float));\n\n output->write ((const char *) &infoBits, sizeof (infoBits));\n output->write ((const char *) &age, sizeof (age));\n output->write ((const char *) &isolationTime, sizeof (isolationTime));\n output->write ((const char *) &viscosity, sizeof (viscosity));\n output->write ((const char *) &density, sizeof (density));\n output->write ((const char *) &pressure, sizeof (pressure));\n output->write ((const char *) &mass, sizeof (mass));\n output->write ((const char *) &temperature, sizeof (temperature));\n output->write ((const char *) &pid, sizeof (pid));\n\n }\n\n\t// per the file format spec, we have to atleast write out the fact that we don't support per-particle data and additional real flow internal data\n\tint zero = 0;\n\toutput->write((const char*)&zero, sizeof(int)); // no per particle data\n\toutput->write((const char*)&zero, sizeof(char)); // no RF 4 data (just 1 byte of 0)\n\toutput->write((const char*)&zero, sizeof(char)); // no RF 5 data (just 1 byte of 0)\n\n return true;\n}\n\n}// end of namespace Partio\n" }, { "path": "Externals/partio/io/GEO.cpp", "content": "/*\nPARTIO SOFTWARE\nCopyright 2010 Disney Enterprises, Inc. All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n*/\n\n#include \"../Partio.h\"\n#include \"../core/ParticleHeaders.h\"\n#include \"ZIP.h\"\n\n#include \n#include \n#include \n#include \n#include \n\n\nnamespace Partio\n{\n\nusing namespace std;\n\ntemplate\nvoid readGeoAttr(istream& f,const ParticleAttribute& attr,ParticleAccessor& accessor,ParticlesDataMutable::iterator& iterator)\n{\n //cout<<\"reading \"<::TYPE TYPE;\n TYPE* data=accessor.raw(iterator);\n for(int k=0;k>data[k];\n }\n}\n\nvoid writeString(std::ostream& output,const char* s){\n const char* p=s;\n output<<\"\\\"\";\n while(*p != 0){\n if(*p=='\\\\' || *p=='\"') output<<'\\\\';\n output<<*p;\n p++;\n }\n output<<\"\\\"\";\n}\n\nstring scanString(istream& input)\n{\n // TODO: this code does not check for buf overrun\n // TODO: this code doesn't properly check for FEOF condition\n char buf[4096];\n char *ptr=buf;\n char c;\n while(input.good()){\n input.get(c);\n if(!isspace(c)) break;\n }\n if(!input.good()) return \"\";\n\n if(c!='\"'){\n while(input.good()){\n *ptr++=c;\n input.get(c);\n if(isspace(c)) break;\n }\n }else{\n while(input.good()){\n input.get(c);\n if(c=='\\\\'){\n input.get(c);\n *ptr++=c;\n }else if(c=='\"'){\n break;\n }else{\n *ptr++=c;\n }\n }\n }\n *ptr++=0;\n return string(buf);\n}\n\nParticlesDataMutable* readGEO(const char* filename,const bool headersOnly,std::ostream* errorStream)\n{\n unique_ptr input(Gzip_In(filename,ios::in));\n if(!*input){\n if(errorStream) *errorStream<<\"Partio: Can't open particle data file: \"<good()){\n *input>>word;\n if(word==\"NPoints\") *input>>NPoints;\n else if(word==\"NPointAttrib\"){*input>>NPointAttrib;break;}\n }\n // skip until PointAttrib\n while(input->good()){\n *input>>word;\n if(word==\"PointAttrib\") break;\n }\n // read attribute descriptions\n int attrInfoRead = 0;\n \n ParticleAttribute positionAttr=simple->addAttribute(\"position\",VECTOR,3);\n ParticleAccessor positionAccessor(positionAttr);\n\n vector attrs;\n vector accessors;\n while (input->good() && attrInfoRead < NPointAttrib) {\n string attrName, attrType;\n int nvals = 0;\n *input >> attrName >> nvals >> attrType;\n if(attrType==\"index\"){\n if(errorStream) *errorStream<<\"Partio: attr '\"<>nIndices;\n ParticleAttribute attribute=simple->addAttribute(attrName.c_str(),INDEXEDSTR,1);\n attrs.push_back(attribute);\n for(int j=0;j>indexName;\n indexName=scanString(*input);\n if (!headersOnly) {\n int id=simple->registerIndexedStr(attribute,indexName.c_str());\n if(id != j){\n if(errorStream) *errorStream<<\"Partio: error on read, expected registerIndexStr to return index \"<>defval;\n }\n ParticleAttributeType type;\n // TODO: fix for other attribute types\n if(attrType==\"float\") type=FLOAT;\n else if(attrType==\"vector\") type=VECTOR;\n else if(attrType==\"int\") type=INT;\n else{\n if(errorStream) *errorStream<<\"Partio: unknown attribute \"<addAttribute(attrName.c_str(),type,nvals));\n accessors.push_back(ParticleAccessor(attrs.back()));\n attrInfoRead++;\n }\n }\n\n simple->addParticles(NPoints);\n\n ParticlesDataMutable::iterator iterator=simple->begin();\n iterator.addAccessor(positionAccessor);\n for(size_t i=0;iend();iterator!=end && input->good();++iterator){\n float* posInternal=positionAccessor.raw(iterator); \n for(int i=0;i<3;i++) *input>>posInternal[i];\n *input>>fval;\n //cout<<\"saw \"<> paren;\n if (paren != '(') break;\n \n // read additional attribute values\n for (unsigned int i=0;i(*input,attrs[i],accessors[i],iterator);break;\n case VECTOR: readGeoAttr(*input,attrs[i],accessors[i],iterator);break;\n case INT: readGeoAttr(*input,attrs[i],accessors[i],iterator);break;\n case INDEXEDSTR: readGeoAttr(*input,attrs[i],accessors[i],iterator);break;\n }\n }\n // skip closing parenthes\n *input >> paren;\n if (paren != ')') break;\n }\n return simple;\n}\n\n\ntemplate\nvoid writeType(ostream& output,const ParticlesData&,const ParticleAttribute& attrib,\n const ParticleAccessor& accessor,const ParticlesData::const_iterator& iterator)\n{\n const T* data=accessor.raw(iterator);\n for(int i=0;i0) output<<\" \";\n output< output(\n compressed ? \n Gzip_Out(filename,ios::out)\n :new ofstream(filename,ios::out));\n\n *output<<\"PGEOMETRY V5\"<0) *output<<\"PointAttrib\"< handles;\n vector accessors;\n for(int i=0;i& indexes=p.indexedStrs(attrib);\n *output<& point=positionAccessor.data >(iterator);\n *output<0) *output<<\"\\t\";\n ParticleAttribute& handle=handles[aindex];\n ParticleAccessor& accessor=accessors[aindex];\n switch(handle.type){\n case NONE: assert(false);break;\n case FLOAT: writeType::TYPE>(*output,p,handle,accessor,iterator);break;\n case INT: writeType::TYPE>(*output,p,handle,accessor,iterator);break;\n case VECTOR: writeType::TYPE>(*output,p,handle,accessor,iterator);break;\n case INDEXEDSTR: writeType::TYPE>(*output,p,handle,accessor,iterator);break;\n }\n } \n if(handles.size()) *output<<\")\";\n *output<\n#include \n#include \n#include \n#include \n\nnamespace Partio\n{\n//#define PartioBIG_ENDIAN\n\nusing namespace std;\n\n// TODO: convert this to use iterators like the rest of the readers/writers\n\nstd::string GetString(std::istream& input, unsigned int size){\n char* tmp = new char [size];\n input.read(tmp, size);\n std::string result(tmp);\n\n // fix read tag error (ex: DBLA --> DBLAi, why !!)\n if(result.size() > size){\n result.resize(size);\n }\n\n delete [] tmp;\n return result;\n}\n\ntypedef struct{\n std::string name;\n std::string type;\n unsigned int numParticles;\n unsigned int blocksize;\n} Attribute_Header;\n\n\nbool ReadAttrHeader(std::istream& input, Attribute_Header& attribute){\n char tag[4];\n input.read(tag, 4); // CHNM\n\n int chnmSize;\n read(input, chnmSize);\n if(chnmSize%4 > 0){\n chnmSize = chnmSize - chnmSize%4 + 4;\n }\n attribute.name = GetString(input, chnmSize);\n attribute.name = attribute.name.substr(attribute.name.find_first_of(\"_\")+1);\n\n input.read(tag, 4); // SIZE\n int dummy;\n read(input, dummy); // 4\n\n read(input, attribute.numParticles);\n\n attribute.type = GetString(input, 4);\n\n read(input, attribute.blocksize);\n\n return true;\n}\n\nint CharArrayLen(char** charArray){\n int i = 0;\n if(charArray != NULL){\n while(charArray[i] != NULL){\n i++;\n }\n }\n return i;\n}\n\nbool IsStringInCharArray(std::string target, char** list){\n //std::cout << \"Is \" << target << \" in \";\n for(int i = 0; i < CharArrayLen(list); i++){\n //std::cout << std::string(list[i]) << \" \";\n if(target == std::string(list[i])){\n //std::cout << \"? (YES)\" << std::endl;\n return true;\n }\n }\n //std::cout << \"? (NO)\" << std::endl;\n return false;\n}\n\nstatic const int MC_MAGIC = ((((('F'<<8)|'O')<<8)|'R')<<8)|'4';\nstatic const int HEADER_SIZE = 56;\n\nParticlesDataMutable* readMC(const char* filename, const bool headersOnly,std::ostream* errorStream){\n\n std::unique_ptr input(Gzip_In(filename,std::ios::in|std::ios::binary));\n if(!*input){\n if(errorStream) *errorStream << \"Partio: Unable to open file \" << filename << std::endl;\n return 0;\n }\n\n int magic;\n read(*input, magic);\n if(MC_MAGIC != magic){\n if(errorStream) *errorStream << \"Partio: Magic number '\" << magic << \"' of '\" << filename << \"' doesn't match mc magic '\" << MC_MAGIC << \"'\" << std::endl;\n return 0;\n }\n\n int headerSize;\n read(*input, headerSize);\n\n int dummy; // tmp1, tmp2, num1, tmp3, tmp4, num2, num3, tmp5, num4, num5, blockTag\n for(int i = 0; i < 10; i++){\n read(*input, dummy);\n //std::cout << dummy << std::endl;\n }\n\n char tag[4];\n input->read(tag, 4); // FOR4\n\n int blockSize;\n read(*input, blockSize);\n\n // Allocate a simple particle with the appropriate number of points\n ParticlesDataMutable* simple=0;\n if(headersOnly){\n simple = new ParticleHeaders;\n }\n else{\n simple=create();\n }\n\n int numParticles = 0;\n input->read(tag, 4); // MYCH\n while(((int)input->tellg()-HEADER_SIZE) < blockSize){\n Attribute_Header attrHeader;\n ReadAttrHeader(*input, attrHeader);\n\n if(attrHeader.name == std::string(\"id\")){\n numParticles = attrHeader.numParticles;\n }\n\n if(attrHeader.blocksize/sizeof(double) == 1){ // for who ?\n input->seekg((int)input->tellg() + attrHeader.blocksize);\n continue;\n }\n#if 0 // TODO: if we ever put back attributes re-enable this\n if(attributes && (IsStringInCharArray(attrHeader.name, attributes)==false)){\n input->seekg((int)input->tellg() + attrHeader.blocksize);\n continue;\n }\n#endif\n\n if(attrHeader.type == std::string(\"FVCA\")){\n input->seekg((int)input->tellg() + attrHeader.blocksize);\n simple->addAttribute(attrHeader.name.c_str(), VECTOR, 3);\n }\n else if(attrHeader.type == std::string(\"DBLA\")){\n\t\t\tinput->seekg((int)input->tellg() + attrHeader.blocksize);\n\t\t\tif(attrHeader.name == \"id\"){\n\t\t\t\tsimple->addAttribute(attrHeader.name.c_str(), INT, 1);\n\t\t\t}\n else{\n\t\t\t\tsimple->addAttribute(attrHeader.name.c_str(), FLOAT, 1);\n\t\t\t}\n }\n else\n\t\t{\n input->seekg((int)input->tellg() + attrHeader.blocksize);\n if(errorStream) *errorStream << \"Partio: Attribute '\" << attrHeader.name << \" \" << attrHeader.type << \"' cannot map type\" << std::endl;\n }\n }\n simple->addParticles(numParticles);\n\n // If all we care about is headers, then return.--\n if(headersOnly){\n return simple;\n }\n //cout << \"==============================================================\" << endl;\n input->seekg(HEADER_SIZE);\n input->read(tag, 4); // MYCH\n while((int)input->tellg()-HEADER_SIZE < blockSize){\n Attribute_Header attrHeader;\n ReadAttrHeader(*input, attrHeader);\n\n if(attrHeader.blocksize/sizeof(double) == 1){ // for who ?\n input->seekg((int)input->tellg() + attrHeader.blocksize);\n continue;\n }\n\n ParticleAttribute attrHandle;\n if(simple->attributeInfo(attrHeader.name.c_str(), attrHandle) == false){\n input->seekg((int)input->tellg() + attrHeader.blocksize);\n continue;\n }\n\n Partio::ParticlesDataMutable::iterator it = simple->begin();\n Partio::ParticleAccessor accessor(attrHandle);\n it.addAccessor(accessor);\n\n\t\t//std::cout << attrHeader.name << std::endl;\n if (attrHeader.type == std::string(\"DBLA\")){\n\t\t\tif (attrHeader.name == \"id\")\n\t\t\t{\n\t\t\t\tfor (int i = 0; i < simple->numParticles(); i++)\n\t\t\t\t{\n double tmp;\n read(*input, tmp);\n int* data = simple->dataWrite(attrHandle, i);\n data[0] = (int)tmp;\n\t\t\t\t}\n\t\t\t}\n\t\t\telse{\n\t\t\t\tfor (int i = 0; i < simple->numParticles(); i++){\n\t\t\t\t\tdouble tmp;\n\t\t\t\t\tread(*input, tmp);\n\t\t\t\t\tfloat* data = simple->dataWrite(attrHandle, i);\n\t\t\t\t\tdata[0] = (float)tmp;\n\t\t\t\t}\n\t\t\t}\n }\n else if(attrHeader.type == std::string(\"FVCA\")){\n for(Partio::ParticlesDataMutable::iterator end = simple->end(); it != end; ++it){\n input->read(accessor.raw(it), sizeof(float)*attrHandle.count);\n }\n it = simple->begin();\n for(Partio::ParticlesDataMutable::iterator end = simple->end(); it != end; ++it){\n float* data = accessor.raw(it);\n for(int i = 0; i < attrHandle.count; i++){\n BIGEND::swap(data[i]);\n //data[k]=buffer[attrOffsets[attrIndex]+k];\n //data[i] = endianSwap(data[i]);\n }\n }\n\n\n }\n /*\n if(0){\n std::cout << typeName << std::endl;\n std::cerr << \"Partio: \" << filename << \" had unknown attribute spec \" << typeName << \" \" << name << std::endl;\n simple->release();\n return 0;\n }*/\n\n }\n return simple;\n\n}\n/*\nbool dgMc::open(string filePath){\n timeval t1, t2;\n\n ReadStr(file, 4); // MYCH\n\n while(((int)file.tellg()-8-40-8) < header.blockSize){\n ReadStr(file, 4); // CHNM\n\n int chnmSize = ReadInt(file);\n if(chnmSize%4 > 0){\n chnmSize = chnmSize - chnmSize%4 + 4;\n }\n string attrname = ReadChar(file, chnmSize);\n attrname = attrname.substr(attrname.find_first_of(\"_\")+1);\n //cout << attrname << endl;\n\n ReadStr(file, 4); // SIZE\n ReadInt(file);\n\n int arrayLength = ReadInt(file);\n string format = ReadStr(file, 4); // DBLA or FVCA\n int bufferLength = ReadInt(file);\n\n string DBLA(\"DBLA\");\n //cout << format << \" \" << arrayLength << \" \" << bufferLength << endl;\n if(format == string(\"DBLA\")){\n ReadDoubleArray(file, (int)file.tellg(), &_doubleArray[attrname], arrayLength);\n //file.seekg((int)file.tellg() + bufferLength);\n }\n else{ // FVCA\n ReadVectorArray(file, (int)file.tellg(), &_vectorArray[attrname], arrayLength);\n if(attrname == string(\"position\")){\n //ReadVectorArray(file, (int)file.tellg(), &_vectorArray[attrname], arrayLength);\n //file.seekg((int)file.tellg() + bufferLength);\n }\n else{\n\n //file.seekg((int)file.tellg() + bufferLength);\n }\n //return true;\n }\n\n if(attrname == string(\"id\")){\n _numParticles = arrayLength;\n }\n }\n return true;\n}\n\nint main(){\n cout << \"go\" << endl;\n\n timeval t1, t2;\n double elapsedTime;\n gettimeofday(&t1, NULL);\n\n for(int i = 0; i < 1; i++){\n dgMc mc;\n mc.open(string(\"/dept/rdworks/jinkuen/testfile/mc/real_nParticleShape1Frame47.mc\"));\n cout << mc.numParticles() << \" \";\n for(int i = 0; i < mc.count(); i++){\n cout << mc.list(dgParticle::All)[i] << \" \";\n }\n mc.clear();\n }\n cout << endl;\n\n gettimeofday(&t2, NULL);\n elapsedTime = (t2.tv_sec - t1.tv_sec) * 1000.0; // sec to ms\n elapsedTime += (t2.tv_usec - t1.tv_usec) / 1000.0; // us to ms\n cout << elapsedTime << \" ms.\\n\";\n\n return 1;\n}\n\n*/\n\n}\n" }, { "path": "Externals/partio/io/PDA.cpp", "content": "/*\nPARTIO SOFTWARE\nCopyright 2011 Disney Enterprises, Inc. All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n*/\n#include \"../Partio.h\"\n#include \"../core/ParticleHeaders.h\"\n#include \"ZIP.h\"\n\n#include \n#include \n#include \n#include \n#include \n\nnamespace Partio\n{\n\nusing namespace std;\n\n// TODO: convert this to use iterators like the rest of the readers/writers\n\nParticlesDataMutable* readPDA(const char* filename,const bool headersOnly,std::ostream* errorStream)\n{\n unique_ptr input(Gzip_In(filename,ios::in|ios::binary));\n if(!*input){\n if(errorStream) *errorStream <<\"Partio: Can't open particle data file: \"<good()){\n *input>>word;\n if(word!=\"ATTRIBUTES\"){simple->release();return 0;}\n }\n\n vector attrNames;\n vector attrs;\n\n while(input->good()){\n *input>>word;\n if(word==\"TYPES\") break;;\n attrNames.push_back(word);\n }\n\n size_t index=0;\n while(input->good()){\n *input>>word;\n if(word==\"NUMBER_OF_PARTICLES:\") break;\n\n if(index>=attrNames.size()) continue;\n\n if(word==\"V\"){\n attrs.push_back(simple->addAttribute(attrNames[index].c_str(),Partio::VECTOR,3));\n }else if(word==\"R\"){\n attrs.push_back(simple->addAttribute(attrNames[index].c_str(),Partio::FLOAT,1));\n }else if(word==\"I\"){\n attrs.push_back(simple->addAttribute(attrNames[index].c_str(),Partio::INT,1));\n }\n\n index++;\n }\n\n unsigned int num=0;\n if(input->good()){\n *input>>num;\n simple->addParticles(num);\n if(headersOnly) return simple; // escape before we try to touch data\n }else{\n simple->release();\n return 0;\n }\n \n // look for beginning of header\n if(input->good()){\n *input>>word;\n if(word != \"BEGIN\"){simple->release();return 0;}\n }\n if(input->good()){\n *input>>word;\n if(word != \"DATA\"){simple->release();return 0;}\n }\n\n // Read actual particle data\n if(!input->good()){simple->release();return 0;}\n for(unsigned int particleIndex=0;input->good() && particleIndexdataWrite(attrs[attrIndex],particleIndex);\n for(int count=0;count>ival;\n data[count]=ival;\n }\n }else if(attrs[attrIndex].type==Partio::FLOAT || attrs[attrIndex].type==Partio::VECTOR){\n float* data=simple->dataWrite(attrs[attrIndex],particleIndex);\n for(int count=0;count>fval;\n data[count]=fval;\n }\n }\n }\n }\n \n return simple;\n}\n\nbool writePDA(const char* filename,const ParticlesData& p,const bool compressed,std::ostream* errorStream)\n{\n unique_ptr output(\n compressed ? \n Gzip_Out(filename,ios::out|ios::binary)\n :new ofstream(filename,ios::out|ios::binary));\n\n *output<<\"ATTRIBUTES\"< attrs;\n for (int aIndex=0;aIndex(attrs[attrIndex],particleIndex);\n for(int count=0;count(attrs[attrIndex],particleIndex);\n for(int count=0;count\n#include \n#include \n#include \n#include \n#include \n#include \nnamespace Partio\n{\n\nusing namespace std;\n\ntemplate struct PDB_POLICY;\ntemplate<> struct PDB_POLICY<32>\n{\n typedef PDB::PDB_Header32 HEADER;\n typedef PDB::PDBdata32 DATA;\n typedef PDB::Channel32 CHANNEL;\n typedef PDB::Channel_Data32 CHANNEL_DATA;\n typedef PDB::Channel_io_Header CHANNEL_IO;\n};\ntemplate<> struct PDB_POLICY<64>\n{\n typedef PDB::PDB_Header HEADER;\n typedef PDB::PDBdata DATA;\n typedef PDB::Channel CHANNEL;\n typedef PDB::Channel_Data CHANNEL_DATA;\n typedef PDB::Channel_io_Header CHANNEL_IO;\n};\n\nstring GetString(istream& input,bool& error)\n{\n const char terminator='\\0';\n // TODO: make this check for FEOF condition! and also more efficient\n char c=' ';\n string s=\"\";\n error=true;\n while (input)\n {\n input.read(&c,sizeof(char));\n if(c == terminator){error=false;break;}\n s += c;\n }\n return s;\n}\n\n\ntemplate ParticlesDataMutable* readPDBHelper(const char* filename,const bool headersOnly,std::ostream* errorStream)\n{\n\n unique_ptr input(Gzip_In(filename,ios::in|ios::binary));\n if(!*input){\n if(errorStream) *errorStream<<\"Partio: Unable to open file \"<::HEADER header;\n\n input->read((char*)&header,sizeof(typename PDB_POLICY::HEADER));\n if(header.magic != PDB_MAGIC){\n if(errorStream) *errorStream<<\"Partio: failed to get PDB magic\"<addParticles(header.data_size);\n \n for(unsigned int i=0;i::CHANNEL_IO channelIOHeader;\n input->read((char*)&channelIOHeader,sizeof(channelIOHeader));\n typename PDB_POLICY::CHANNEL channelHeader;\n input->read((char*)&channelHeader,sizeof(channelHeader));\n bool error;\n string name=GetString(*input,error);\n if(error){\n simple->release();\n return 0;\n }\n\n typename PDB_POLICY::CHANNEL_DATA channelData;\n input->read((char*)&channelData,sizeof(channelData));\n\n \n ParticleAttributeType type;\n switch(channelHeader.type){\n case PDB_VECTOR: type=VECTOR;break;\n case PDB_REAL: type=FLOAT;break;\n case PDB_LONG: type=INT;break;\n default: type=NONE;break;\n }\n int size=header.data_size*channelData.datasize;\n\n // Read data or skip if we haven't found appropriate type handle\n if(type==NONE){\n char buf[1024];\n int toSkip=size;\n while(toSkip>0){\n input->read(buf,min(toSkip,1024));\n toSkip-=1024;\n }\n if(errorStream) *errorStream<<\"Partio: Attribute '\"<addAttribute(name.c_str(),type,count);\n if(headersOnly){\n char buf[1024];\n int toSkip=size;\n while(toSkip>0){\n input->read(buf,min(toSkip,1024));\n toSkip-=1024;\n }\n }else{\n Partio::ParticlesDataMutable::iterator it=simple->begin();\n Partio::ParticleAccessor accessor(attrHandle);\n it.addAccessor(accessor);\n\n for(Partio::ParticlesDataMutable::iterator end=simple->end();it!=end;++it){\n input->read(accessor.raw(it),sizeof(float)*attrHandle.count);\n }\n }\n }\n }\n return simple;\n}\n\ntemplate\nbool writePDBHelper(const char* filename,const ParticlesData& p,const bool compressed,std::ostream* errorStream)\n{\n unique_ptr output(\n compressed ? \n Gzip_Out(filename,ios::out|ios::binary)\n :new ofstream(filename,ios::out|ios::binary));\n\n if(!*output){\n if(errorStream) *errorStream<<\"Partio Unable to open file \"<::HEADER h32;\n memset(&h32,0,sizeof(typename PDB_POLICY::HEADER));\n h32.magic=PDB_MAGIC;\n h32.swap=1;\n h32.version=1.0;\n h32.time=0.0;\n h32.data_size=p.numParticles();\n h32.num_data=p.numAttributes();\n for(int k=0;k<32;k++) h32.padding[k]=0;\n h32.data=0;\n output->write((char*)&h32,sizeof(typename PDB_POLICY::HEADER));\n \n for(int attrIndex=0;attrIndex::CHANNEL_IO cio;\n typename PDB_POLICY::CHANNEL channel;\n typename PDB_POLICY::CHANNEL_DATA data_header;\n memset(&cio,0,sizeof(typename PDB_POLICY::CHANNEL_IO));\n memset(&channel,0,sizeof(typename PDB_POLICY::CHANNEL));\n memset(&data_header,0,sizeof(typename PDB_POLICY::CHANNEL_DATA));\n\n cio.magic=0;\n cio.swap=1;\n cio.encoding=0;\n cio.type=0;\n output->write((char*)&cio,sizeof(typename PDB_POLICY::CHANNEL_IO));\n \n // TODO: assert cproper count!\n channel.name=0;\n switch(attr.type){\n case INDEXEDSTR:channel.type=PDB_LONG;break;\n case INT:channel.type=PDB_LONG;break;\n case FLOAT:channel.type=PDB_REAL;break;\n case VECTOR:channel.type=PDB_VECTOR;break;\n default: assert(false);\n }\n channel.size=0;\n channel.active_start=0;\n channel.active_end=h32.data_size-1;\n channel.hide=0;\n channel.disconnect=0;\n channel.data=0;\n channel.link=0;\n channel.next=0;\n output->write((char*)&channel,sizeof(channel));\n output->write(attr.name.c_str(),attr.name.length()*sizeof(char)+1);\n data_header.type=channel.type;\n data_header.datasize=attr.count*sizeof(float);\n data_header.blocksize=p.numParticles();\n data_header.num_blocks=1;\n data_header.block=0;\n output->write((char*)&data_header,sizeof(data_header));\n\n Partio::ParticlesData::const_iterator it=p.begin();\n Partio::ParticleAccessor accessor(attr);\n it.addAccessor(accessor);\n\n for(Partio::ParticlesData::const_iterator end=p.end();it!=end;++it){\n output->write(accessor.raw(it),sizeof(float)*attr.count);\n }\n }\n return true;\n}\n\nParticlesDataMutable* readPDB32(const char* filename,const bool headersOnly,std::ostream* errorStream)\n{return readPDBHelper<32>(filename,headersOnly,errorStream);}\n\nParticlesDataMutable* readPDB64(const char* filename,const bool headersOnly,std::ostream* errorStream)\n{return readPDBHelper<64>(filename,headersOnly,errorStream);}\n\nbool writePDB32(const char* filename,const ParticlesData& p,const bool compressed,std::ostream* errorStream)\n{return writePDBHelper<32>(filename,p,compressed,errorStream);}\n\nbool writePDB64(const char* filename,const ParticlesData& p,const bool compressed,std::ostream* errorStream)\n{return writePDBHelper<64>(filename,p,compressed,errorStream);}\n\nParticlesDataMutable* readPDB(const char* filename,const bool headersOnly,std::ostream* errorStream)\n{\n unique_ptr input(Gzip_In(filename,ios::in|ios::binary));\n if(!*input){\n if(errorStream) *errorStream <<\"Partio: Unable to open file \"<::HEADER header;\n input->read((char*)&header,sizeof(header));\n if(header.magic != PDB_MAGIC){\n if(errorStream) *errorStream <<\"Partio: failed to get PDB magic\"<::CHANNEL_IO channelIOHeader;\n input->read((char*)&channelIOHeader,sizeof(channelIOHeader));\n //cout<<\"we got channel io as \"< 5 || channelIOHeader.type < 0 || (channelIOHeader.swap != 1 && channelIOHeader.swap != 0)){\n return readPDBHelper<32>(filename,headersOnly,errorStream);\n }else{\n return readPDBHelper<64>(filename,headersOnly,errorStream);\n }\n}\n\nbool writePDB(const char* filename,const ParticlesData& p,const bool compressed,std::ostream* errorStream)\n{return writePDBHelper<32>(filename,p,compressed,errorStream);}\n\n}\n" }, { "path": "Externals/partio/io/PDC.cpp", "content": "/*\nPARTIO SOFTWARE\nCopyright (c) 2011 Disney Enterprises, Inc. and Contributors, All rights reserved\n\n keypress events also added the PTS file format (all need cleanup)\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n\nFormat Contributed by github user: Jinkuen\nModifications from: github user: redpawfx (redpawFX@gmail.com) and Luma Pictures 2011\n\n*/\n\n#include \"../Partio.h\"\n#include \"../core/ParticleHeaders.h\"\n#include \"PartioEndian.h\"\n#include \"ZIP.h\"\n\n#include \n#include \n#include \n#include \n\nnamespace Partio{\n\nusing namespace std;\n\nstatic const int PDC_MAGIC = (((((' '<<8)|'C')<<8)|'D')<<8)|'P'; // \" CDP\"\n\ntypedef struct{\n int magic;\n int version;\n int bitorder;\n int tmp1;\n int tmp2;\n int numParticles;\n int numAttrs;\n} PDC_HEADER;\n\nstring readName(istream& input){\n int nameLen = 0;\n read(input, nameLen);\n char* name = new char[nameLen];\n input.read(name, nameLen);\n string result(name, name+nameLen);\n delete [] name;\n return result;\n}\n\nParticlesDataMutable* readPDC(const char* filename, const bool headersOnly,std::ostream* errorStream){\n\n unique_ptr input(Gzip_In(filename,std::ios::in|std::ios::binary));\n if(!*input){\n if(errorStream) *errorStream << \"Partio: Unable to open file \" << filename << std::endl;\n return 0;\n }\n\n PDC_HEADER header;\n input->read((char*)&header, sizeof(header));\n if(PDC_MAGIC != header.magic){\n if(errorStream) *errorStream << \"Partio: Magic number '\" << header.magic << \"' of '\" << filename << \"' doesn't match pdc magic '\" << PDC_MAGIC << \"'\" << std::endl;\n return 0;\n }\n\n BIGEND::swap(header.numParticles);\n BIGEND::swap(header.numAttrs);\n\n ParticlesDataMutable* simple = headersOnly ? new ParticleHeaders: create();\n simple->addParticles(header.numParticles);\n\n for(int attrIndex = 0; attrIndex < header.numAttrs; attrIndex++){\n // add attribute\n ParticleAttribute attr;\n string attrName = readName(*input);\n int type;\n read(*input, type);\n if(type == 3){\n attr = simple->addAttribute(attrName.c_str(), FLOAT, 1);\n }\n else if(type == 5){\n attr = simple->addAttribute(attrName.c_str(), VECTOR, 3);\n }\n\n // if headersOnly, skip\n if(headersOnly){\n input->seekg((int)input->tellg() + header.numParticles*sizeof(double)*attr.count);\n continue;\n }\n else{\n double tmp[3];\n for(int partIndex = 0; partIndex < simple->numParticles(); partIndex++){\n for(int dim = 0; dim < attr.count; dim++){\n read(*input, tmp[dim]);\n simple->dataWrite(attr, partIndex)[dim] = (float)tmp[dim];\n }\n }\n }\n }\n\n return simple;\n}\n\nbool writePDC(const char* filename,const ParticlesData& p,const bool compressed,std::ostream* errorStream){\n unique_ptr output(\n compressed ?\n Gzip_Out(filename,ios::out|ios::binary)\n :new std::ofstream(filename,ios::out|ios::binary));\n\n if(!*output){\n if(errorStream) *errorStream << \"Partio Unable to open file \" << filename << endl;\n return false;\n }\n\n // write .pdc header\n write(*output, PDC_MAGIC);\n write(*output, (int)1); // version\n write(*output, (int)1); // bitorder\n write(*output, (int)0); // tmp1\n write(*output, (int)0); // tmp2\n write(*output, (int)p.numParticles());\n write(*output, (int)p.numAttributes());\n\n for(int attrIndex = 0; attrIndex < p.numAttributes(); attrIndex++){\n ParticleAttribute attr;\n p.attributeInfo(attrIndex,attr);\n\n // write attribute name\n write(*output, (int)attr.name.length());\n output->write(attr.name.c_str(), (int)attr.name.length());\n\n // write type\n int count = 1; // FLOAT\n if(attr.type == VECTOR){\n count = 3;\n }\n write(*output, (int)(count+2));\n\n // write data\n for(int partIndex = 0; partIndex < p.numParticles(); partIndex++){\n const float* data = p.data(attr, partIndex);\n for(int dim = 0; dim < count; dim++){\n write(*output, (double)data[dim]);\n }\n }\n }\n return true;\n}\n\n}// end of namespace Partio\n" }, { "path": "Externals/partio/io/PRT.cppbak", "content": "/*\nPARTIO SOFTWARE\nCopyright (c) 2011 Disney Enterprises, Inc. and Contributors, All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n\nFormat Contributed by github user: K240\nSome Code for this format was helped along by referring to an implementation by Bo Schwartzstein and ThinkBox Software THANKS!\nModifications from: github user: redpawfx (redpawFX@gmail.com) and Luma Pictures 2011\n\n\n*/\n#ifndef PARTIO_WIN32\n#ifdef PARTIO_USE_ZLIB\n#include \"../Partio.h\"\n#include \"PartioEndian.h\"\n#include \"../core/ParticleHeaders.h\"\n#include \n\n\n//#define USE_ILMHALF // use Ilm's Half library\n#define AUTO_CASES // auto upcase ie:position => Position\n\n#ifdef USE_ILMHALF\n#include \n#endif\n\n#include \n#include \n#include \n#include \n#include \n#endif\nnamespace Partio{\n\n#define OUT_BUFSIZE\t\t(4096)\n\ntypedef struct FileHeadder {\n unsigned char\tmagic[8];\n unsigned int\theadersize;\n unsigned char\tsignature[32];\n unsigned int\tversion;\n unsigned long long numParticles;\n} PRT_File_Headder;\n\ntypedef struct Channel {\n unsigned char\tname[32];\n unsigned int\ttype;\n unsigned int\tarity;\n unsigned int\toffset;\n} Channel;\n\nstatic unsigned char magic[8] = {192, 'P', 'R', 'T', '\\r', '\\n', 26, '\\n'};\nstatic unsigned char signature[32] = {\n 0x45,0x78,0x74,0x65,0x6e,0x73,0x69,0x62,0x6c,0x65,0x20,0x50,0x61,0x72,0x74,0x69,\n 0x63,0x6c,0x65,0x20,0x46,0x6f,0x72,0x6d,0x61,0x74,0x00,0x00,0x00,0x00,0x00,0x00\n };\n\nstatic unsigned int sizes[11] = {2, 4, 8, 2, 4, 8, 2, 4, 8, 1, 1};\n \n#ifndef USE_ILMHALF\nunion f_ui {\n unsigned int ui;\n float f;\n};\n\nstatic f_ui half2float[65536] = {\n#include \"half2float.h\"\n};\n#endif\n\nstatic bool read_buffer(std::istream& is, z_stream& z, char* in_buf, void* p, size_t size, std::ostream* errorStream) {\n z.next_out=(Bytef*)p;\n z.avail_out=(uInt)size;\n\n while (z.avail_out) {\n if ( z.avail_in == 0 ) {\n if (!is.eof()) {\n z.next_in = (Bytef*)in_buf;\n is.read((char*)z.next_in, OUT_BUFSIZE);\n if (is.bad()) {\n if(errorStream) *errorStream<<\"read error \"< 0) {\n std::cerr<<\"Truncated prt file \"< input(new std::ifstream(filename,std::ios::in|std::ios::binary));\n if (!*input) {\n if(errorStream) *errorStream<<\"Partio: Unable to open file \"<read((char*)&header,sizeof(FileHeadder));\n\n if (memcmp(header.magic, magic, sizeof(magic))) {\n if(errorStream) *errorStream<<\"Partio: failed to get PRT magic\"< sizeof(FileHeadder))\n input->seekg(header.headersize);\n \n int reserve=0;\n int channels=0;\n int channelsize=0;\n read(*input,reserve);\t\t// reserved\n read(*input,channels);\t\t// number of channel\n read(*input,channelsize);\t// size of channel\n\n simple->addParticles((const int)header.numParticles);\n\n std::vector chans;\n std::vector attrs;\n \n unsigned particleSize = 0;\n \n for (int i=0; iread((char*)&ch, sizeof(Channel));\n ParticleAttributeType type=NONE;\n switch (ch.type) {\n case 0:\t// int16\n case 1:\t// int32\n case 2:\t// int64\n type = INT;\n break;\n case 3:\t// float16\n case 4:\t// float32\n case 5:\t// float64\n if (ch.arity == 3)\n type = VECTOR;\n else\n type = FLOAT;\n break;\n case 6:\t// uint16\n case 7:\t// uint32\n case 8:\t// uint64\n type = INT;\n break;\n case 9:\t// int8\n case 10:// uint8\n type = INT;\n break;\n }\n if (type != NONE) {\n#ifdef AUTO_CASES\n if (ch.name[0] >= 'A' && ch.name[0] <= 'Z') {\n ch.name[0] += 0x20;\n }\n#endif\n std::string name((char*)ch.name);\n ParticleAttribute attrHandle=simple->addAttribute(name.c_str(),type,ch.arity);\n chans.push_back(ch);\n attrs.push_back(attrHandle);\n }\n \n // The size of the particle is determined from the channel with largest offset. The channels are not required to be listed in order.\n particleSize = (std::max)( particleSize, chans.back().offset + sizes[ch.type] );\n \n // The channel entry might have more data in other PRT versions.\n if ((unsigned)channelsize > sizeof(Channel))\n input->seekg(channelsize - sizeof(Channel), std::ios::cur);\n }\n\n if (headersOnly) return simple;\n\n z_stream z;\n z.zalloc = Z_NULL;z.zfree = Z_NULL;z.opaque = Z_NULL;\n if (inflateInit( &z ) != Z_OK) {\n if(errorStream) *errorStream<<\"Zlib inflateInit error\"<numParticles();particleIndex++) {\n // Read the particle from the file, and decompress it into a single particle-sized buffer.\n read_buffer(*input, z, (char*)in_buf, prt_buf, particleSize, errorStream);\n \n for (unsigned int attrIndex=0;attrIndexdataWrite(attrs[attrIndex],particleIndex);\n for (int count=0;count( &prt_buf[ chans[attrIndex].offset + count * sizeof(short) ] );\n }\n break;\n case 1:\t// int32\n {\n ival = (int)*reinterpret_cast( &prt_buf[ chans[attrIndex].offset + count * sizeof(int) ] );\n }\n break;\n case 2:\t// int64\n {\n ival = (int)*reinterpret_cast( &prt_buf[ chans[attrIndex].offset + count * sizeof(long long) ] );\n }\n break;\n case 6:\t// uint16\n {\n ival = (int)*reinterpret_cast( &prt_buf[ chans[attrIndex].offset + count * sizeof(unsigned short) ] );\n }\n break;\n case 7:\t// uint32\n {\n ival = (int)*reinterpret_cast( &prt_buf[ chans[attrIndex].offset + + count * sizeof(unsigned int) ] );\n }\n break;\n case 8:\t// uint64\n {\n ival = (int)*reinterpret_cast( &prt_buf[ chans[attrIndex].offset + count * sizeof(unsigned long long) ] );\n }\n break;\n case 9:\t// int8\n {\n ival = (int)prt_buf[ chans[attrIndex].offset + count ];\n }\n break;\n case 10:// uint8\n {\n ival = (int)*reinterpret_cast( &prt_buf[ chans[attrIndex].offset + count * sizeof(unsigned char) ] );\n }\n break;\n }\n data[count]=ival;\n }\n }else if (attrs[attrIndex].type==Partio::FLOAT || attrs[attrIndex].type==Partio::VECTOR) {\n float* data=simple->dataWrite(attrs[attrIndex],particleIndex);\n for (int count=0;count( &prt_buf[ chans[attrIndex].offset + count * sizeof(half) ] );\n#else\n unsigned short val = *reinterpret_cast( &prt_buf[ chans[attrIndex].offset + count * sizeof(unsigned short) ] );\n fval = half2float[val].f;\n#endif\n }\n break;\n case 4:\t// float32\n {\n fval = (float)*reinterpret_cast( &prt_buf[ chans[attrIndex].offset + count * sizeof(float) ] );\n }\n break;\n case 5:\t// float64\n {\n fval = (float)*reinterpret_cast( &prt_buf[ chans[attrIndex].offset + count * sizeof(double) ] );\n }\n break;\n }\n data[count]=fval;\n }\n }\n\t\t}\n\t}\n \n delete[] prt_buf;\n \n if (inflateEnd( &z ) != Z_OK) {\n if(errorStream) *errorStream<<\"Zlib inflateEnd error\"< output(\n new std::ofstream(filename,std::ios::out|std::ios::binary));\n\n if (!*output) {\n if(errorStream) *errorStream <<\"Partio Unable to open file \"<write((char*)&header,sizeof(FileHeadder));\n write(*output, reserve);\n write(*output, (int)p.numAttributes());\n reserve = 0x2c;\n write(*output, reserve);\n\n std::vector attrs;\n int offset = 0;\n for (int i=0;i= 'a' && ch.name[0] <= 'z') {\n ch.name[0] -= 0x20;\n }\n #endif\n output->write((char*)&ch,sizeof(Channel));\n attrs.push_back(attr);\n }\n }\n\n z_stream z;\n z.zalloc = Z_NULL;z.zfree = Z_NULL;z.opaque = Z_NULL;\n if (deflateInit( &z, Z_DEFAULT_COMPRESSION ) != Z_OK) {\n if(errorStream) *errorStream<<\"Zlib deflateInit error\"<(attrs[attrIndex],particleIndex);\n if (!write_buffer(*output, z, (char*)out_buf, (void*)data, sizeof(int)*attrs[attrIndex].count, false, errorStream))\n return false;\n } else if (attrs[attrIndex].type==Partio::FLOAT || attrs[attrIndex].type==Partio::VECTOR) {\n const float* data=p.data(attrs[attrIndex],particleIndex);\n if (!write_buffer(*output, z, (char*)out_buf, (void*)data, sizeof(int)*attrs[attrIndex].count, false, errorStream))\n return false;\n }\n }\n }\n write_buffer(*output, z, (char*)out_buf, 0, 0, true, errorStream);\n if (deflateEnd( &z ) != Z_OK) {\n if(errorStream) *errorStream<<\"Zlib deflateEnd error\"< 0\n return true;\n}\n\n}\n#else\n#include \"../Partio.h\"\n#include \n#include \n\n\nnamespace Partio{\nParticlesDataMutable* readPRT(const char* filename,const bool headersOnly, std::ostream* error)\n{\n std::cerr<<\"PRT not supported on windows\"<\n\n#include \"../Partio.h\"\n#include \"../core/ParticleHeaders.h\"\n#include \"PartioEndian.h\"\n#include \"ZIP.h\"\n\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n\nnamespace Partio\n{\n\nusing namespace std;\n\nstatic const int ptc_magic=((((('c'<<8)|'t')<<8)|'p')<<8)|'p';\n\n\ninline string GetString(istream& input,const char terminator='\\0')\n{\n // TODO: make this check for FEOF condition! and also more efficient\n char c=' ';\n string s;\n while (c!=terminator && input)\n {\n input.read(&c,sizeof(char));\n\ts += c;\n }\n return s;\n}\n\nbool ParseSpec(const string& spec,string& typeName,string& name)\n{\n // TODO: make more robust\n const char* s=spec.c_str();\n typeName=\"\";name=\"\";\n while(*s!=' ') typeName+=*s++;\n while(*s==' ') s++;\n while(*s!='\\n') name+=*s++;\n return true;\n}\n\nParticlesDataMutable* readPTC(const char* filename,const bool headersOnly,std::ostream* errorStream)\n{\n unique_ptr input(Gzip_In(filename,ios::in|ios::binary));\n if(!*input){\n if(errorStream) *errorStream <<\"Partio: Unable to open file \"<(*input,magic);\n if(ptc_magic!=magic){\n if(errorStream) *errorStream <<\"Partio: Magic number '\"<(*input,version);\n if(version>2){\n if(errorStream) *errorStream <<\"Partio: ptc reader only supports version 2 or less\"<(*input,nPoints);\n\n // TODO: allow access to this in the headers only mode for times when only bbox is necessary\n float xmin,ymin,zmin,xmax,ymax,zmax;\n read(*input,xmin,ymin,zmin,xmax,ymax,zmax);\n\n float dummy;\n // Who knows what this is?\n if (version>=1) for (int d=0;d<4;d++) read(*input,dummy);\n // This seems to be 4 bytes of something and 32 0xDEADBEEF guys\n if (version>=2){\n float maxRadius;\n read(*input,maxRadius);\n for (int d=0;d<32;d++) read(*input,dummy);\n }\n\n // world-to-eye\n for(int i=0;i<16;i++) read(*input,dummy);\n // eye-to-screen\n for(int i=0;i<16;i++) read(*input,dummy);\n\n float imgWidth,imgHeight,imgDepth;\n read(*input,imgWidth,imgHeight,imgDepth);\n\n int nVars,dataSize;\n read(*input,nVars,dataSize);\n\n // Allocate a simple particle with the appropriate number of points\n ParticlesDataMutable* simple=0;\n if(headersOnly) simple=new ParticleHeaders;\n else simple=create();\n simple->addParticles((int)nPoints);\n\n // PTC files always have something for these items, so allocate the data\n vector attrHandles;\n ParticleAttribute positionHandle=simple->addAttribute(\"position\",VECTOR,3);\n ParticleAttribute normalHandle=simple->addAttribute(\"normal\",VECTOR,3);\n ParticleAttribute radiusHandle=simple->addAttribute(\"radius\",FLOAT,1);\n string typeName,name;\n\n // data types are \"float\", \"point\", \"vector\", \"normal\", \"color\", or \"matrix\"\n int parsedSize=0;\n for(int chanNum=0;chanNumrelease();\n return 0;\n }\n \n // make unqiue name\n int unique=1;\n string effectiveName=name;\n ParticleAttribute info;\n while(simple->attributeInfo(effectiveName.c_str(),info)){\n ostringstream ss;\n ss<addAttribute(effectiveName.c_str(),dataType,dataSize));\n parsedSize+=dataSize;\n }\n if(dataSize!=parsedSize){\n if(errorStream) *errorStream <<\"Partio: error with PTC, computed dataSize (\"<release();\n return 0;\n }\n\n // If all we care about is headers, then return. \n if(headersOnly){\n return simple;\n }\n\n // more weird input attributes\n if(version>=1) for(int i=0;i<2;i++) read(*input,dummy);\n\n for(int pointIndex=0;pointIndexdataWrite(positionHandle,pointIndex);\n read(*input,pos[0],pos[1],pos[2]);\n\n unsigned short phi,z; // normal encoded\n read(*input,phi,z);\n float* norm=simple->dataWrite(normalHandle,pointIndex);\n\n\t// Convert unsigned short (phi,nz) to xyz normal\n // This packing code is based on Per Christensen's rman forum post\n\tif (phi != 65535 || z != 65535) {\n\t float nz = (float)z / 65535.0f;\n\t norm[2] = 2.0f * nz - 1.0f;\n\t float fphi = (float)phi / 65535.0f;\n\t fphi = 2.0f * static_cast(M_PI) * (fphi - 0.5f);\n\t //assert(-M_PI-0.0001 <= fphi && fphi <= M_PI+0.0001);\n\t float rxy = sqrt(1.0f - norm[2]*norm[2]);\n\t norm[0] = rxy * sin(fphi);\n\t norm[1] = rxy * cos(fphi);\n\t} else {\n\t norm[0] = norm[1] = norm[2] = 0.0f;\n\t} \n\n float* radius=simple->dataWrite(radiusHandle,pointIndex);\n read(*input,radius[0]);\n\n\n for(unsigned int i=0;idataWrite(attrHandles[i],pointIndex);\n for(int j=0;j(*input,data[j]);\n }\n\n }\n\n return simple;\n}\n\nbool writePTC(const char* filename,const ParticlesData& p,const bool compressed,std::ostream* errorStream)\n{\n //ofstream output(filename,ios::out|ios::binary);\n\n unique_ptr output(\n compressed ? \n Gzip_Out(filename,ios::out|ios::binary)\n :new ofstream(filename,ios::out|ios::binary));\n\n if(!*output){\n if(errorStream) *errorStream <<\"Partio Unable to open file \"<(*output,ptc_magic);\n write(*output,(int)0);\n\n // particle count\n double numParticlesAsDouble=p.numParticles();\n write(*output,numParticlesAsDouble);\n\n ParticleAttribute positionHandle,normalHandle,radiusHandle;\n bool foundPosition=p.attributeInfo(\"position\",positionHandle);\n bool foundNormal=p.attributeInfo(\"normal\",normalHandle);\n bool foundRadius=p.attributeInfo(\"radius\",radiusHandle);\n\n if(!foundPosition){\n if(errorStream) *errorStream <<\"Partio: failed to find attr 'position' for PTC output\"<(positionHandle,i);\n for(int k=0;k<3;k++){\n boxmin[k]=min(pos[k],boxmin[k]);\n boxmax[k]=max(pos[k],boxmax[k]);\n }\n }\n write(*output,boxmin[0],boxmin[1],boxmin[2]);\n write(*output,boxmax[0],boxmax[1],boxmax[2]);\n\n // world-to-eye & \n for(int i=0;i<4;i++) for(int j=0;j<4;j++){\n if(i==j) write(*output,(float)1);\n else write(*output,(float)0);\n }\n // eye-to-screen\n const float foo[4][4]={{1.8f,0,0,0}, {0,2.41f,0,0}, {0,0,1,1}, {0,0,-.1f,0}};\n for(int i=0;i<4;i++) for(int j=0;j<4;j++){\n write(*output,foo[i][j]);\n }\n \n\n // imgwidth imgheight, imgdepth\n write(*output,(float)640,(float)480,(float)300);\n\n int nVars=0,dataSize=0;\n vector specs;\n vector attrs;\n for(int i=0;i(*output,nVars,dataSize);\n\n for(unsigned int i=0;iwrite(specs[i].c_str(),specs[i].length());\n }\n\n for(int pointIndex=0;pointIndex(positionHandle,pointIndex);\n write(*output,pos[0],pos[1],pos[2]);\n // write normal\n static const float static_n[3]={0,0,0};\n const float* n=static_n;\n if(foundNormal)\n n=p.data(normalHandle,pointIndex);\n // normalize and encode normals as two unsigned short integers z and\n // phi, representing the z coordinate and angle in the xy plane. The\n // special value z == phi == 65535 encodes a zero normal.\n\tint phi, z;\n\tif (n[0] == 0 && n[1] == 0 && n[2] == 0) phi = z = 65535;\n\telse {\n float mag_squared=n[0]*n[0]+n[1]*n[1]+n[2]*n[2];\n\t phi = int((atan2(n[0], n[1]) * (1/(2*M_PI)) + 0.5) * 65535 + 0.5);\n\t z = std::min(int((n[2]/sqrt(mag_squared)+1)/2 * 65535 + 0.5), 65535);\n // phi is redundent when z == 65535; avoid the special value.\n if (phi == 65535 && z == 65535)\n phi = 0;\n\t}\n write(*output,(unsigned short)phi,(unsigned short)z);\n // write radius\n static const float static_r[1]={1.f};\n const float* radius=static_r;\n if(foundRadius)\n radius=p.data(radiusHandle,pointIndex);\n write(*output,radius[0]);\n // write other attributes\n for(unsigned int i=0;i(attrs[i],pointIndex);\n for(int k=0;k(*output,data[k]);\n }\n }\n \n }\n return true;\n}\n\n}\n" }, { "path": "Externals/partio/io/PTS.cpp", "content": "/*\nPARTIO SOFTWARE\nCopyright (c) 2011 Disney Enterprises, Inc. and Contributors, All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n\nFormat Contributed by github user: redpawfx (redpawFX@gmail.com) and Luma Pictures 2011\nSome code for this format was helped along by referring to an implementation by\n*/\n#include \"../Partio.h\"\n#include \"../core/ParticleHeaders.h\"\n#include \"ZIP.h\"\n\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n\nnamespace Partio\n{\n\nusing namespace std;\n\n// TODO: convert this to use iterators like the rest of the readers/writers\n\nParticlesDataMutable* readPTS(const char* filename,const bool headersOnly,std::ostream* errorStream)\n{\n unique_ptr input(Gzip_In(filename,ios::in|ios::binary));\n if (!*input)\n {\n if(errorStream) *errorStream<<\"Partio: Can't open particle data file: \"< attrNames;\n vector attrs;\n\n\t/// we're going to fake the ID attribute since there's no such thing in PTS Files\n\tattrNames.push_back((string)\"id\");\n\tattrs.push_back(simple->addAttribute(attrNames[0].c_str(),Partio::INT,1));\n\n /// FORMAT is up to 8 elements space delimited { posX posY posZ remission quality red green blue }\n // since there's no header data to parse we're just going to hard code this\n\n /* Start from the beginning */\n\tinput->seekg(0,ios::beg);\n\n /* Determine amount of values per line */\n char line[1024];\n /* Jump over first line. */\n\tinput->getline(line,1024);\n input->getline(line,1024);\n int valcount = 0;\n#ifdef PARTIO_WIN32\n\tchar * nextLine = NULL;\n char * pch = strtok_s( line, \"\\t \", &nextLine );\n#else\n\tchar * pch = strtok( line, \"\\t \" );\n#endif\n while ( pch )\n {\n if ( *pch != 0 && *pch != '\\n' )\n\t\t{\n valcount++;\n }\n#ifdef PARTIO_WIN32\n pch = strtok_s( NULL, \"\\t \", &nextLine );\n#else\n\t\tpch = strtok( NULL, \"\\t \" );\n#endif\n }\n\n\n switch ( valcount )\n\t{\n\t\tcase 3: // position only\n\t\t{\n\t\t\tattrNames.push_back((string)\"position\");\n\t\t\tattrs.push_back(simple->addAttribute(attrNames[1].c_str(),Partio::VECTOR,3));\n\t\t}\n\t\tbreak;\n\t\tcase 4: // position and remission\n\t\t{\n\t\t\tattrNames.push_back((string)\"position\");\n\t\t\tattrNames.push_back((string)\"remission\");\n\t\t\tattrs.push_back(simple->addAttribute(attrNames[1].c_str(),Partio::VECTOR,3));\n\t\t\tattrs.push_back(simple->addAttribute(attrNames[2].c_str(),Partio::FLOAT,1));\n\t\t}\n\t\tbreak;\n\t\tcase 6: // position and RGB\n\t\t{\n\t\t\tattrNames.push_back((string)\"position\");\n\t\t\tattrNames.push_back((string)\"pointColor\");\n\t\t\tattrs.push_back(simple->addAttribute(attrNames[1].c_str(),Partio::VECTOR,3));\n\t\t\tattrs.push_back(simple->addAttribute(attrNames[2].c_str(),Partio::VECTOR,3));\n\t\t}\n\t\tbreak;\n\t\tcase 7: // position remission and RGB\n\t\t{\n\t\t\tattrNames.push_back((string)\"position\");\n\t\t\tattrNames.push_back((string)\"remission\");\n\t\t\tattrNames.push_back((string)\"pointColor\");\n\t\t\tattrs.push_back(simple->addAttribute(attrNames[1].c_str(),Partio::VECTOR,3));\n\t\t\tattrs.push_back(simple->addAttribute(attrNames[2].c_str(),Partio::FLOAT,1));\n\t\t\tattrs.push_back(simple->addAttribute(attrNames[3].c_str(),Partio::VECTOR,3));\n\t\t}\n\t\tbreak;\n\t\tcase 8: // everything\n\t\t{\n\t\t\tattrNames.push_back((string)\"position\");\n\t\t\tattrNames.push_back((string)\"remission\");\n\t\t\tattrNames.push_back((string)\"quality\");\n\t\t\tattrNames.push_back((string)\"pointColor\");\n\t\t\tattrs.push_back(simple->addAttribute(attrNames[1].c_str(),Partio::VECTOR,3));\n\t\t\tattrs.push_back(simple->addAttribute(attrNames[2].c_str(),Partio::FLOAT,1));\n\t\t\tattrs.push_back(simple->addAttribute(attrNames[3].c_str(),Partio::INT,1));\n\t\t\tattrs.push_back(simple->addAttribute(attrNames[4].c_str(),Partio::VECTOR,3));\n\t\t}\n\t\tbreak;\n\t\tdefault:\n\t\t{\n\t\t\treturn 0;\n\t\t}\n\t\tbreak;\n\n }\n\n input->seekg(0,ios::beg);\n\n unsigned int num=0;\n simple->addParticles(num);\n if (headersOnly) return simple; // escape before we try to touch data\n\n if (input->good())\n { // garbage count at top of file\n\t\tchar junk[1024];\n input->getline(junk,1024);\n }\n\n // Read actual particle data\n if (!input->good()) {\n simple->release();\n return 0;\n }\n\n // we have to read line by line, because data is not clean and consistent so we skip any lines that dont' conform\n\n for (unsigned int particleIndex=0;input->good();)\n {\n string token = \"\";\n char line[1024];\n input->getline(line, 1024);\n\n stringstream ss(line);\n\n float lineData[8];\n int i = 0;\n\n while (ss >> token)\n {\n stringstream foo(token);\n float x;\n foo >> x;\n\t\t\tlineData[i] = x;\n i++;\n }\n\n if (i == valcount)\n {\n simple->addParticle();\n for (unsigned int attrIndex=0;attrIndexdataWrite(attrs[attrIndex],particleIndex);\n\t\t\t\t\tif (attrs[attrIndex].name == \"id\")\n\t\t\t\t\t{\n\t\t\t\t\t\tdata[0]=particleIndex;\n\t\t\t\t\t}\n\t\t\t\t\telse\n\t\t\t\t\t{\n\t\t\t\t\t\tdata[0] = (int)lineData[4];\n\t\t\t\t\t}\n\n\n }\n else if (attrs[attrIndex].type==Partio::FLOAT || attrs[attrIndex].type==Partio::VECTOR)\n {\n float* data=simple->dataWrite(attrs[attrIndex],particleIndex);\n\n\t\t\t\t\tif (attrs[attrIndex].name == \"pointColor\")\n\t\t\t\t\t{\n\t\t\t\t\t\t// 8 bit color conversion\n\t\t\t\t\t\tdata[0]=lineData[4]/255;\n\t\t\t\t\t\tdata[1]=lineData[5]/255;\n\t\t\t\t\t\tdata[2]=lineData[6]/255;\n\t\t\t\t\t}\n\t\t\t\t\telse if (attrs[attrIndex].name == \"position\")\n\t\t\t\t\t{\n\t\t\t\t\t\t// position, we flip y/z\n\t\t\t\t\t\tdata[0]=lineData[0];\n\t\t\t\t\t\tdata[1]=lineData[2];\n\t\t\t\t\t\tdata[2]=lineData[1];\n\t\t\t\t\t}\n\t\t\t\t\telse if (attrs[attrIndex].name == \"remission\")\n\t\t\t\t\t{\n\t\t\t\t\t\tdata[0] = lineData[3];\n\t\t\t\t\t}\n\n }\n }\n particleIndex++;\n }\n }\n return simple;\n}\n\n/// THIS DOESENT WORK YET>>\n/*\nbool writePTS(const char* filename,const ParticlesData& p,const bool compressed)\n{\n unique_ptr output(\n compressed ?\n Gzip_Out(filename,ios::out|ios::binary)\n :new ofstream(filename,ios::out|ios::binary));\n\n *output<<\"ATTRIBUTES\"< attrs;\n for (int aIndex=0;aIndex(attrs[attrIndex],particleIndex);\n for(int count=0;count(attrs[attrIndex],particleIndex);\n for(int count=0;count\n#include \"../core/Mutex.h\"\n#include \"../Partio.h\"\n#include \"readers.h\"\n\nnamespace Partio{\nusing namespace std;\n\n// reader and writer code\ntypedef ParticlesDataMutable* (*READER_FUNCTION)(const char*,const bool,std::ostream*);\ntypedef bool (*WRITER_FUNCTION)(const char*,const ParticlesData&,const bool,std::ostream*);\n\nPartioMutex initializationMutex;\n\nmap&\nreaders()\n{\n static map data;\n static bool initialized=false;\n if(!initialized){\n\tinitializationMutex.lock();\n data[\"bgeo\"]=readBGEO;\n data[\"bhclassic\"]=readBGEO;\n data[\"geo\"]=readGEO;\n data[\"hclassic\"]=readGEO;\n data[\"pdb\"]=readPDB;\n data[\"pdb32\"]=readPDB32;\n data[\"pdb64\"]=readPDB64;\n data[\"pda\"]=readPDA;\n data[\"mc\"]=readMC;\n data[\"ptc\"]=readPTC;\n data[\"pdc\"]=readPDC;\n //data[\"prt\"]=readPRT;\n data[\"bin\"]=readBIN;\n data[\"pts\"]=readPTS;\n data[\"ptf\"]=readPTC;\n data[\"itbl\"]=readBGEO;\n data[\"atbl\"]=readBGEO;\n\tinitialized=true;\n\tinitializationMutex.unlock();\n }\n return data;\n}\n\nmap&\nwriters()\n{\n static map data;\n static bool initialized=false;\n if(!initialized){\n\tinitializationMutex.lock();\n data[\"bgeo\"]=writeBGEO;\n data[\"bhclassic\"]=writeBGEO;\n data[\"geo\"]=writeGEO;\n data[\"hclassic\"]=writeGEO;\n data[\"pdb\"]=writePDB;\n data[\"pdb32\"]=writePDB32;\n data[\"pdb64\"]=writePDB64;\n data[\"pda\"]=writePDA;\n data[\"ptc\"]=writePTC;\n data[\"rib\"]=writeRIB;\n data[\"pdc\"]=writePDC;\n //data[\"prt\"]=writePRT;\n data[\"bin\"]=writeBIN;\n data[\"ptf\"]=writePTC;\n data[\"itbl\"]=writeBGEO;\n data[\"atbl\"]=writeBGEO;\n\tinitialized=true;\n\tinitializationMutex.unlock();\n }\n return data;\n}\n\n//! Gives extension of a file ignoring any trailing .gz\n//! i.e. for 'foo.pdb.gz' it gives 'pdb', for 'foo.pdb' it gives 'pdb'\nbool extensionIgnoringGz(const string& filename,string& ret,bool &endsWithGz,std::ostream& errorStream)\n{\n size_t period=filename.rfind('.');\n endsWithGz=false;\n if(period==string::npos){\n errorStream<<\"Partio: No extension detected in filename\"<::iterator i=readers().find(extension);\n if(i==readers().end()){\n errorStream<<\"Partio: No reader defined for extension \"<second)(c_filename,false,verbose ? &errorStream : 0);\n}\n\nParticlesInfo*\nreadHeaders(const char* c_filename,bool verbose,std::ostream& errorStream)\n{\n string filename(c_filename);\n string extension;\n bool endsWithGz;\n if(!extensionIgnoringGz(filename,extension,endsWithGz,errorStream)) return 0;\n map::iterator i=readers().find(extension);\n if(i==readers().end()){\n errorStream<<\"Partio: No reader defined for extension \"<second)(c_filename,true,verbose ? &errorStream : 0);\n}\n\nvoid\nwrite(const char* c_filename,const ParticlesData& particles,const bool forceCompressed,bool verbose,std::ostream& errorStream)\n{\n string filename(c_filename);\n string extension;\n bool endsWithGz;\n if(!extensionIgnoringGz(filename,extension,endsWithGz,errorStream)) return;\n map::iterator i=writers().find(extension);\n if(i==writers().end()){\n errorStream<<\"Partio: No writer defined for extension \"<second)(c_filename,particles,forceCompressed || endsWithGz,verbose ? &errorStream : 0);\n}\n\n} // namespace Partio\n" }, { "path": "Externals/partio/io/PartioEndian.h", "content": "/*\nPARTIO SOFTWARE\nCopyright 2010 Disney Enterprises, Inc. All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n*/\n\n#ifndef _partioendian_h_\n#define _partioendian_h_\n\n#include \n#include \n\nnamespace Partio{\n\ntemplate\nvoid endianSwap(T& value)\n{\n T temp=value;\n char* src=(char*)&temp;\n char* dest=(char*)&value;\n for(unsigned int i=0;i static void swap(T&){\n }\n};\n\nstruct LITEND {\n template static void swap(T& x){\n endianSwap(x);\n }\n};\n#else\nstruct BIGEND {\n template static void swap(T& x){\n endianSwap(x);\n }\n};\n\nstruct LITEND {\n template static void swap(T&){\n }\n};\n#endif\n\ntemplate inline void\nread(std::istream& input,T& d)\n{\n input.read((char*)&d,sizeof(T));\n E::swap(d);\n}\n\ntemplate inline void\nwrite(std::ostream& output,const T& d)\n{\n T copy=d;\n E::swap(copy);\n output.write((char*)©,sizeof(T));\n}\n\ntemplate\nvoid read(std::istream& input,T1& d1,T2& d2)\n{read(input,d1);read(input,d2);}\n\ntemplate\nvoid read(std::istream& input,T1& d1,T2& d2,T3& d3)\n{read(input,d1);read(input,d2,d3);}\n\ntemplate\nvoid read(std::istream& input,T1& d1,T2& d2,T3& d3,T4& d4)\n{read(input,d1);read(input,d2,d3,d4);}\n\ntemplate\nvoid read(std::istream& input,T1& d1,T2& d2,T3& d3,T4& d4,T5& d5)\n{read(input,d1);read(input,d2,d3,d4,d5);}\n\ntemplate\nvoid read(std::istream& input,T1& d1,T2& d2,T3& d3,T4& d4,T5& d5,T6& d6)\n{read(input,d1);read(input,d2,d3,d4,d5,d6);}\n\ntemplate\nvoid write(std::ostream& output,const T1& d1,const T2& d2)\n{write(output,d1);write(output,d2);}\n\ntemplate\nvoid write(std::ostream& output,const T1& d1,const T2& d2,const T3& d3)\n{write(output,d1);write(output,d2,d3);}\n\ntemplate\nvoid write(std::ostream& output,const T1& d1,const T2& d2,const T3& d3,const T4& d4)\n{write(output,d1);write(output,d2,d3,d4);}\n\ntemplate\nvoid write(std::ostream& output,const T1& d1,const T2& d2,const T3& d3,const T4& d4,const T5& d5)\n{write(output,d1);write(output,d2,d3,d4,d5);}\n\ntemplate\nvoid write(std::ostream& output,const T1& d1,const T2& d2,const T3& d3,const T4& d4,const T5& d5,const T6& d6)\n{write(output,d1);write(output,d2,d3,d4,d5,d6);}\n\n}\n#endif\n" }, { "path": "Externals/partio/io/RIB.cpp", "content": "/*\n* Copyright (c) 2010 - 2011 Sebastien Noury \n*\n* Permission is hereby granted, free of charge, to any person obtaining a copy\n* of this software and associated documentation files (the \"Software\"), to deal\n* in the Software without restriction, including without limitation the rights\n* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n* copies of the Software, and to permit persons to whom the Software is\n* furnished to do so, subject to the following conditions:\n*\n* The above copyright notice and this permission notice shall be included in\n* all copies or substantial portions of the Software.\n*\n* THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n* THE SOFTWARE.\n*\n*/\n\n#include \"../Partio.h\"\n#include \"../core/ParticleHeaders.h\"\n#include \"ZIP.h\"\n\n#include \n#include \n#include \n#include \n#include \n\nnamespace Partio\n{\n\nusing namespace std;\n\nbool writeRIB(const char* filename, const ParticlesData& p, const bool compressed,std::ostream* errorStream)\n{\n unique_ptr output(\n compressed ? Gzip_Out(filename, ios::out | ios::binary)\n : new ofstream(filename, ios::out | ios::binary));\n\n ParticleAttribute dummy;\n bool foundP = p.attributeInfo(\"position\", dummy) || p.attributeInfo(\"P\", dummy);\n bool foundP2 = p.attributeInfo(\"position2\", dummy) || p.attributeInfo(\"P2\", dummy);\n bool foundWidth = p.attributeInfo(\"radius\", dummy) || p.attributeInfo(\"width\", dummy) || p.attributeInfo(\"radiusPP\", dummy);\n\n if (!foundP)\n {\n if(errorStream) *errorStream << \"Partio: failed to find attr 'position' or 'P' for RIB output\" << endl;\n return false;\n }\n\n if (!foundWidth)\n if(errorStream) *errorStream << \"Partio: failed to find attr 'width','radius', or 'radiusPP' for RIB output, using constantwidth = 1\" << endl;\n\n *output << \"version 3.04\" << endl;\n\n if (foundP2)\n *output << \"GeometricApproximation \\\"motionfactor\\\" 1.0\" << endl;\n\n *output << \"AttributeBegin\" << endl;\n *output << \" ResourceBegin\" << endl;\n *output << \" Attribute \\\"identifier\\\" \\\"name\\\" [\\\"|partioParticle1|partioParticleShape1\\\"]\" << endl;\n\n int numPasses = foundP2 ? 2 : 1;\n\n if (foundP2)\n *output << \" MotionBegin [0.0 1.0]\" << endl;\n\n for (int passIndex = 0; passIndex < numPasses; ++passIndex)\n {\n *output << (foundP2 ? \" \" : \"\") << \" Points \";\n\n for (int attrIndex = 0; attrIndex < p.numAttributes(); ++attrIndex)\n {\n ParticleAttribute attr;\n p.attributeInfo(attrIndex, attr);\n\n if ((passIndex == 0 && (attr.name == \"P2\" || attr.name == \"position2\")) ||\n (passIndex == 1 && (attr.name == \"P\" || attr.name == \"position\"))) continue;\n\n string attrname = (attr.name == \"position\" || attr.name == \"position2\" || attr.name == \"P\" || attr.name == \"P2\")\n ? \"P\"\n : (attr.name == \"radius\" ? \"width\" : attr.name);\n\n *output << \"\\\"\" << attrname << \"\\\" [ \";\n\t\t\tint spaceCount = 0;\n switch (attr.type)\n {\n case Partio::FLOAT:\n case Partio::VECTOR:\n\t\t\t{\n for (int particleIndex = 0; particleIndex < p.numParticles(); ++particleIndex)\n {\n const float *data = p.data(attr, particleIndex);\n for (int count = 0; count < attr.count; ++count)\n\t\t\t\t\t{\n *output << data[count] << \" \";\n\t\t\t\t\t\tspaceCount ++;\n\t\t\t\t\t}\n if (spaceCount > 12)\n {\n *output << \"\\n \";\n spaceCount = 0;\n }\n }\n break;\n\t\t\t}\n case Partio::INT:\n\t\t\t{\n for (int particleIndex = 0; particleIndex < p.numParticles(); ++particleIndex)\n {\n const int *data = p.data(attr, particleIndex);\n for (int count = 0; count < attr.count; ++count)\n\t\t\t\t\t{\n *output << data[count] << \" \";\n\t\t\t\t\t\tspaceCount ++;\n\t\t\t\t\t}\n\t\t\t\t\tif (spaceCount > 12)\n {\n *output << \"\\n \";\n spaceCount = 0;\n }\n }\n break;\n\t\t\t}\n case Partio::NONE:\n default:\n break;\n }\n\n *output << \"]\\n \";\n }\n\n if (!foundWidth)\n *output << \"\\\"constantwidth\\\" [1.0]\";\n\n *output << endl;\n }\n\n if (foundP2)\n *output << \" MotionEnd\" << endl;\n\n *output << \" ResourceEnd\" << endl;\n *output << \"AttributeEnd\" << endl;\n\n return true;\n}\n}\n" }, { "path": "Externals/partio/io/ZIP.cpp", "content": "/*\nPARTIO SOFTWARE\nCopyright 2010 Disney Enterprises, Inc. All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n*/\n\n#ifdef PARTIO_USE_ZLIB\nextern \"C\"{\n# include \n}\n#endif\n\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n\n#include \"ZIP.h\"\n\nnamespace Partio{\n\n\n \ntemplate\ninline void Swap_Endianity(T& x)\n{\n assert(sizeof(T)<=8);\n if(sizeof(T)>1) {\n T old=x;\n for(unsigned int k=1;k<=sizeof(T);k++) ((char*)&x)[k-1]=((char*)&old)[sizeof(T)-k];\n }\n}\n\ntemplate\ninline void Read_Primitive(std::istream& stream,T& x)\n{\n stream.read(&(char&)x,sizeof(T));\n}\n\ntemplate\ninline void Write_Primitive(std::ostream& stream,const T& x)\n{\n stream.write(&(char&)x,sizeof(T));\n}\n\n\n//#####################################################################\n// class GZipFileHeader\n//#####################################################################\nstruct GZipFileHeader\n{\n unsigned char magic0,magic1; // magic should be 0x8b,0x1f\n unsigned char cm; // compression method 0x8 is gzip\n unsigned char flags; // flags\n unsigned int modtime; // 4 byte modification time\n unsigned char flags2; // secondary flags\n unsigned char os; // operating system 0xff for unknown\n unsigned short crc16; // crc check\n unsigned int crc32;\n\n GZipFileHeader()\n :magic0(0),magic1(0),flags(0),modtime(0),flags2(0),os(0),crc16(0),crc32(0)\n {}\n\n bool Read(std::istream& istream)\n {Read_Primitive(istream,magic0);\n Read_Primitive(istream,magic1);\n if(magic0 != 0x1f || magic1 != 0x8b){//std::cerr<<\"gzip: did not find gzip magic 0x1f 0x8b\"<(istream.gcount());\n total_read+=strm.avail_in;\n strm.next_in=(Bytef*)in;}\n int ret=inflate(&strm,Z_NO_FLUSH); // decompress\n switch(ret){\n case Z_STREAM_ERROR: \n std::cerr<<\"libz error Z_STREAM_ERROR\"<(istream.gcount());\n total_read+=count;\n return count;}\n }\n\n virtual int underflow()\n {if(gptr() && (gptr()(gptr()-eback());\n if(put_back_count>4) put_back_count=4;\n std::memmove(out+(4-put_back_count),gptr()-put_back_count,put_back_count);\n int num=process();\n setg((char*)(out+4-put_back_count),(char*)(out+4),(char*)(out+4+num));\n if(num<=0) return EOF;\n return traits_type::to_int_type(*gptr());}\n\n virtual int overflow(int)\n {assert(false);return EOF;}\n\n\t// assignment operator declared and not defined, to suppress warning 4512 for Visual Studio\n\tZipStreambufDecompress& operator=(const ZipStreambufDecompress& _Right);\n\n//#####################################################################\n};\n\n//#####################################################################\n// class ZipStreambufCompress\n//#####################################################################\nclass ZipStreambufCompress:public std::streambuf\n{\n static const int buffer_size=512;\n std::ostream& ostream; // owned when header==0 (when not part of zip file)\n\n z_stream strm;\n unsigned char in[buffer_size],out[buffer_size];\n\n ZipFileHeader* header;\n GZipFileHeader gzip_header;\n unsigned int header_offset;\n unsigned int uncompressed_size;\n unsigned int crc;\n\n bool valid;\n\npublic:\n ZipStreambufCompress(ZipFileHeader* header,std::ostream& stream)\n :ostream(stream),header(header),valid(true)\n {\n strm.zalloc=Z_NULL;strm.zfree=Z_NULL;strm.opaque=Z_NULL;\n int ret=deflateInit2(&strm,Z_DEFAULT_COMPRESSION,Z_DEFLATED,-MAX_WBITS,8,Z_DEFAULT_STRATEGY); \n if(ret != Z_OK){std::cerr<<\"libz: failed to deflateInit\"<header_offset=static_cast(stream.tellp());header->Write(ostream,false);}\n else{header_offset=static_cast(stream.tellp());gzip_header.Write(ostream);}\n uncompressed_size=crc=0;\n }\n\n virtual ~ZipStreambufCompress()\n {if(valid){\n process(true);\n deflateEnd(&strm);\n if(header){\n std::ios::streampos final_position=ostream.tellp();\n header->uncompressed_size=uncompressed_size;\n header->crc=crc;\n ostream.seekp(header->header_offset);\n header->Write(ostream,false);\n ostream.seekp(final_position);}\n else{Write_Primitive(ostream,crc);Write_Primitive(ostream,uncompressed_size);}}\n if(!header) delete &ostream;}\n\nprotected:\n int process(bool flush)\n {if(!valid) return -1;\n strm.next_in=(Bytef*)pbase();\n strm.avail_in=static_cast(pptr()-pbase());\n while(strm.avail_in!=0 || flush){\n strm.avail_out=buffer_size;\n strm.next_out=(Bytef*)out;\n int ret=deflate(&strm,flush?Z_FINISH:Z_NO_FLUSH);\n if(!(ret!=Z_BUF_ERROR && ret!=Z_STREAM_ERROR)){\n valid=false;\n std::cerr<<\"gzip: gzip error \"<(strm.next_out-(Bytef*)out);\n ostream.write((char*)out,generated_output);\n if(header) header->compressed_size+=generated_output;\n if(ret==Z_STREAM_END) break;}\n // update counts, crc's and buffers\n int consumed_input=static_cast(pptr()-pbase());\n uncompressed_size+=consumed_input;\n crc=crc32(crc,(Bytef*)in,consumed_input);\n setp(pbase(),pbase()+buffer_size-4);return 1;}\n\n virtual int sync()\n {if(pptr() && pptr()>pbase()) return process(false);return 0;}\n\n virtual int underflow()\n {std::runtime_error(\"Attempt to read write only ostream\");return 0;}\n\n virtual int overflow(int c=EOF)\n {if(c!=EOF){*pptr()=static_cast(c);pbump(1);}\n if(process(false)==EOF) return EOF;\n return c;}\n\n\t// assignment operator declared and not defined, to suppress warning 4512 for Visual Studio\n\tZipStreambufCompress& operator=(const ZipStreambufCompress& _Right);\n\n//#####################################################################\n};\n//#####################################################################\n// Class ZIP_FILE_ISTREAM\n//#####################################################################\n// Class needed because istream cannot own its streambuf\nclass ZIP_FILE_ISTREAM:public std::istream\n{\n ZipStreambufDecompress buf;\npublic:\n ZIP_FILE_ISTREAM(std::istream& istream,bool part_of_zip_file)\n :std::istream(&buf),buf(istream,part_of_zip_file)\n {}\n\n virtual ~ZIP_FILE_ISTREAM()\n {}\n\n//#####################################################################\n};\n//#####################################################################\n// Class ZIP_FILE_OSTREAM\n//#####################################################################\n// Class needed because ostream cannot own its streambuf\nclass ZIP_FILE_OSTREAM:public std::ostream\n{\n ZipStreambufCompress buf;\npublic:\n ZIP_FILE_OSTREAM(ZipFileHeader* header,std::ostream& ostream)\n :std::ostream(&buf),buf(header,ostream)\n {}\n\n virtual ~ZIP_FILE_OSTREAM()\n {}\n\n//#####################################################################\n};\n//#####################################################################\n// Function ZipFileWriter\n//#####################################################################\nZipFileWriter::\nZipFileWriter(const std::string& filename)\n{\n ostream.open(filename.c_str(),std::ios::out|std::ios::binary);\n if(!ostream) throw std::runtime_error(\"ZIP: Invalid file handle\");\n}\n//#####################################################################\n// Function ZipFileWriter\n//#####################################################################\nZipFileWriter::\n~ZipFileWriter()\n{\n // Write all file headers\n std::ios::streampos final_position=ostream.tellp();\n for(unsigned int i=0;iWrite(ostream,true);delete files[i];}\n std::ios::streampos central_end=ostream.tellp();\n // Write end of central\n Write_Primitive(ostream,(unsigned int)0x06054b50); // end of central\n Write_Primitive(ostream,(unsigned short)0); // this disk number\n Write_Primitive(ostream,(unsigned short)0); // this disk number\n Write_Primitive(ostream,(unsigned short)files.size()); // one entry in center in this disk\n Write_Primitive(ostream,(unsigned short)files.size()); // one entry in center \n Write_Primitive(ostream,(unsigned int)(central_end-final_position)); // size of header\n Write_Primitive(ostream,(unsigned int)final_position); // offset to header\n Write_Primitive(ostream,(unsigned short)0); // zip comment\n}\n//#####################################################################\n// Function ZipFileWriter\n//#####################################################################\nstd::ostream* ZipFileWriter::\nAdd_File(const std::string& filename,const bool)\n{\n files.push_back(new ZipFileHeader(filename));\n return new ZIP_FILE_OSTREAM(files.back(),ostream);\n}\n//#####################################################################\n// Function ZipFileReader\n//#####################################################################\nZipFileReader::\nZipFileReader(const std::string& filename)\n{\n istream.open(filename.c_str(),std::ios::in|std::ios::binary);\n if(!istream) throw std::runtime_error(\"ZIP: Invalid file handle\");\n Find_And_Read_Central_Header();\n}\n//#####################################################################\n// Function ZipFileReader\n//#####################################################################\nZipFileReader::\n~ZipFileReader()\n{\n std::map::iterator i=filename_to_header.begin();\n for(;i!=filename_to_header.end();++i)\n delete i->second;\n}\n//#####################################################################\n// Function Find_And_Read_Central_Header\n//#####################################################################\nbool ZipFileReader::\nFind_And_Read_Central_Header()\n{\n // Find the header\n // NOTE: this assumes the zip file header is the last thing written to file...\n istream.seekg(0,std::ios_base::end);\n std::ios::streampos end_position=istream.tellg();\n unsigned int max_comment_size=0xffff; // max size of header\n unsigned int read_size_before_comment=22;\n std::ios::streamoff read_start=max_comment_size+read_size_before_comment;\n if(read_start>end_position) read_start=end_position;\n istream.seekg(end_position-read_start);\n char *buf=new char[static_cast(read_start)];\n if(read_start<=0){std::cerr<<\"ZIP: Invalid read buffer size\"<Read(istream,true);\n if(valid) filename_to_header[header->filename]=header;}\n return true;\n}\n//#####################################################################\n// Function Get_File\n//#####################################################################\nstd::istream* ZipFileReader::Get_File(const std::string& filename,const bool)\n{\n std::map::iterator i=filename_to_header.find(filename);\n if(i!=filename_to_header.end()){\n ZipFileHeader* header=i->second;\n istream.seekg((*header).header_offset);return new ZIP_FILE_ISTREAM(istream,true);\n }\n return 0;\n}\n//#####################################################################\n// Function Get_File_List\n//#####################################################################\nvoid ZipFileReader::Get_File_List(std::vector& filenames) const\n{\n filenames.clear();\n std::map::const_iterator i=filename_to_header.begin();\n for(;i!=filename_to_header.end();++i)\n filenames.push_back(i->first);\n}\n//#####################################################################\n// Function Gzip_In\n//#####################################################################\nstd::istream* \nGzip_In(const std::string& filename,std::ios::openmode mode)\n{\n std::ifstream* infile=new std::ifstream(filename.c_str(),mode | std::ios::binary);\n GZipFileHeader header;\n bool zipped=header.Read(*infile);\n infile->seekg(0);\n if(!zipped) return infile;\n else return new ZIP_FILE_ISTREAM(*infile,false);\n}\n//#####################################################################\n// Function Gzip_Out\n//#####################################################################\nstd::ostream* \nGzip_Out(const std::string& filename,std::ios::openmode mode)\n{\n std::ofstream* outfile=new std::ofstream(filename.c_str(),mode);\n return new ZIP_FILE_OSTREAM(0,*outfile);\n}\n//#####################################################################\n\n#else\n\n//#####################################################################\n// Function Gzip_In\n//#####################################################################\nstd::istream* \nGzip_In(const std::string& filename,std::ios::openmode mode)\n{\n std::ifstream* infile=new std::ifstream(filename.c_str(),mode | std::ios::binary);\n GZipFileHeader header;\n bool zipped=header.Read(*infile);\n \n infile->seekg(0);\n if(!zipped) return infile;\n \n delete infile;\n std::cerr<<\"Partio: encountered gz file '\"<\n#include \n#include \n#include \n#include \n#include \n\nnamespace Partio{\nstruct ZipFileHeader;\n//#####################################################################\n// Functions Gzip_Out/Gzip_In - Create streams that read/write .gz\n//#####################################################################\nstd::istream* Gzip_In(const std::string& filename,std::ios::openmode mode);\nstd::ostream* Gzip_Out(const std::string& filename,std::ios::openmode mode);\n//#####################################################################\n// Class ZipFileWriter\n//#####################################################################\nclass ZipFileWriter\n{\n std::ofstream ostream;\n std::vector files;\npublic:\n\n//#####################################################################\n ZipFileWriter(const std::string& filename);\n virtual ~ZipFileWriter();\n std::ostream* Add_File(const std::string& filename,const bool binary=true);\n//#####################################################################\n};\n\n//#####################################################################\n// Class ZipFileReader\n//#####################################################################\nclass ZipFileReader\n{\n std::ifstream istream;\npublic:\n std::map filename_to_header;\n \n//#####################################################################\n ZipFileReader(const std::string& filename);\n virtual ~ZipFileReader();\n std::istream* Get_File(const std::string& filename,const bool binary=true);\n void Get_File_List(std::vector& filenames) const;\nprivate:\n bool Find_And_Read_Central_Header();\n//#####################################################################\n};\n}\n#endif\n" }, { "path": "Externals/partio/io/half2float.h", "content": "{ 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}, { "path": "Externals/partio/io/pdb.h", "content": "/*\nPARTIO SOFTWARE\nCopyright 2010 Disney Enterprises, Inc. All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n\nThis code is based on the Gifts/readpdb directory of Autodesk Maya\n\nNOTE: some modifications were made and \"32-bit\" versions of the\nstructures were created to allow us to assume the pointers were\n32-bit integers instead of system dependent pointers. As originally\ndefined, this format would be architecture dependent (behave\ndifferently on 32-bit and 64-bit architectures). Maya's writers\nmay or may not also be doing this. If you have any files that\ndon't work, please let me know. But in general, it would be\ndifficult/error prone to detect what type the PDB file is. \n\n*/\n\n\n#define PDB_VECTOR 1\n#define PDB_REAL 2\n#define PDB_LONG 3\n#define PDB_CHAR 4\n#define PDB_POINTERT 5\n\ntypedef float Real;\n\ntypedef struct { Real x,y,z; } Vector;\n\n\ntypedef struct Channel_Data32 {\n int type;\n unsigned int datasize;\n unsigned int blocksize;\n int num_blocks;\n unsigned int block; //was void **block;\n} Channel_Data32;\n\ntypedef struct {\n int type;\n unsigned int datasize;\n unsigned int blocksize;\n int num_blocks;\n void **block;\n} Channel_Data;\n\ntypedef struct Channel {\n\n char *name;\n int type;\n unsigned int size;\n unsigned int active_start;\n unsigned int active_end;\n\n char hide;\n char disconnect;\n Channel_Data *data;\n\n struct Channel *link;\n struct Channel *next; } Channel;\n\ntypedef struct Channel32 {\n unsigned int name;\n int\t\t\t\t\t\ttype;\n unsigned int size;\n unsigned int active_start;\n unsigned int active_end;\n\n char hide;\n char disconnect;\n unsigned int data;\n\n unsigned int link;\n unsigned int next;\n} Channel32;\n\n\n\ntypedef struct {\n\n char magic;\n unsigned short swap;\n char encoding;\n char type; } Channel_io_Header;\n\ntypedef struct {\n\n int numAttributes;\n int numParticles;\n float time;\n short *types;\n char **names;\n void **data; } PDBdata;\n\ntypedef struct {\n\n int numAttributes;\n int numParticles;\n float time;\n short *types;\n char **names;\n unsigned int data; } PDBdata32;\n#define\tPDB_MAGIC 670\n\n\ntypedef\tstruct {\n\n int\t\t\t magic;\n unsigned short\t swap;\n float\t\t version;\n float\t\t time;\n unsigned\t\t data_size;\n unsigned\t\t num_data;\n\n char\t\t padding[32];\n\n Channel\t\t **data;\t \n\t}\t PDB_Header;\n\n\ntypedef struct {\n int magic;\n unsigned short swap;\n float version;\n float time;\n unsigned data_size;\n unsigned num_data;\n\n char padding[32];\n\n unsigned int data; \n}\t\tPDB_Header32;\n\n" }, { "path": "Externals/partio/io/readers.h", "content": "/*\nPARTIO SOFTWARE\nCopyright 2011 Disney Enterprises, Inc. All rights reserved\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n* Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.\n\n* The names \"Disney\", \"Walt Disney Pictures\", \"Walt Disney Animation\nStudios\" or the names of its contributors may NOT be used to\nendorse or promote products derived from this software without\nspecific prior written permission from Walt Disney Pictures.\n\nDisclaimer: THIS SOFTWARE IS PROVIDED BY WALT DISNEY PICTURES AND\nCONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\nBUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE, NONINFRINGEMENT AND TITLE ARE DISCLAIMED.\nIN NO EVENT SHALL WALT DISNEY PICTURES, THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND BASED ON ANY\nTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n*/\n#ifndef _READERS_h_\n#define _READERS_h_\n\nnamespace Partio{\nParticlesDataMutable* readBGEO(\tconst char* filename,const bool headersOnly,std::ostream* errorStream);\nParticlesDataMutable* readGEO(\tconst char* filename,const bool headersOnly,std::ostream* errorStream);\nParticlesDataMutable* readPDB(\tconst char* filename,const bool headersOnly,std::ostream* errorStream);\nParticlesDataMutable* readPDB32(const char* filename,const bool headersOnly,std::ostream* errorStream);\nParticlesDataMutable* readPDB64(const char* filename,const bool headersOnly,std::ostream* errorStream);\nParticlesDataMutable* readPDA(\tconst char* filename,const bool headersOnly,std::ostream* errorStream);\nParticlesDataMutable* readMC(\tconst char* filename,const bool headersOnly,std::ostream* errorStream);\nParticlesDataMutable* readPTC(\tconst char* filename,const bool headersOnly,std::ostream* errorStream);\nParticlesDataMutable* readPDC(\tconst char* filename,const bool headersOnly,std::ostream* errorStream);\n//ParticlesDataMutable* readPRT(\tconst char* filename,const bool headersOnly,std::ostream* errorStream);\nParticlesDataMutable* readBIN(\tconst char* filename,const bool headersOnly,std::ostream* errorStream);\nParticlesDataMutable* readPTS( const char* filename,const bool headersOnly,std::ostream* errorStream);\n\nbool writeBGEO(const char* filename,const ParticlesData& p,const bool compressed,std::ostream* errorStream);\nbool writeGEO(const char* filename,const ParticlesData& p,const bool compressed,std::ostream* errorStream);\nbool writePDB(const char* filename,const ParticlesData& p,const bool compressed,std::ostream* errorStream);\nbool writePDB32(const char* filename,const ParticlesData& p,const bool compressed,std::ostream* errorStream);\nbool writePDB64(const char* filename,const ParticlesData& p,const bool compressed,std::ostream* errorStream);\nbool writePDA(const char* filename,const ParticlesData& p,const bool compressed,std::ostream* errorStream);\nbool writePTC(const char* filename,const ParticlesData& p,const bool compressed,std::ostream* errorStream);\nbool writeRIB(const char* filename,const ParticlesData& p,const bool compressed,std::ostream* errorStream);\nbool writePDC(const char* filename,const ParticlesData& p,const bool compressed,std::ostream* errorStream);\n//bool writePRT(const char* filename,const ParticlesData& p,const bool compressed,std::ostream* errorStream);\nbool writeBIN(const char* filename,const ParticlesData& p,const bool compressed,std::ostream* errorStream);\n}\n\n#endif\n" }, { "path": "Externals/variant/mpark/config.hpp", "content": "// MPark.Variant\n//\n// Copyright Michael Park, 2015-2017\n//\n// Distributed under the Boost Software License, Version 1.0.\n// (See accompanying file LICENSE.md or copy at http://boost.org/LICENSE_1_0.txt)\n\n#ifndef MPARK_CONFIG_HPP\n#define MPARK_CONFIG_HPP\n\n// MSVC 2015 Update 3.\n#if __cplusplus < 201103L && (!defined(_MSC_VER) || _MSC_FULL_VER < 190024210)\n#error \"MPark.Variant requires C++11 support.\"\n#endif\n\n#ifndef __has_attribute\n#define __has_attribute(x) 0\n#endif\n\n#ifndef __has_builtin\n#define __has_builtin(x) 0\n#endif\n\n#ifndef __has_include\n#define __has_include(x) 0\n#endif\n\n#ifndef __has_feature\n#define __has_feature(x) 0\n#endif\n\n#if __has_attribute(always_inline) || defined(__GNUC__)\n#define MPARK_ALWAYS_INLINE __attribute__((__always_inline__)) inline\n#elif defined(_MSC_VER)\n#define MPARK_ALWAYS_INLINE __forceinline\n#else\n#define MPARK_ALWAYS_INLINE inline\n#endif\n\n#if __has_builtin(__builtin_addressof) || \\\n (defined(__GNUC__) && __GNUC__ >= 7) || defined(_MSC_VER)\n#define MPARK_BUILTIN_ADDRESSOF\n#endif\n\n#if __has_builtin(__builtin_unreachable) || defined(__GNUC__)\n#define MPARK_BUILTIN_UNREACHABLE __builtin_unreachable()\n#elif defined(_MSC_VER)\n#define MPARK_BUILTIN_UNREACHABLE __assume(false)\n#else\n#define MPARK_BUILTIN_UNREACHABLE\n#endif\n\n#if __has_builtin(__type_pack_element)\n#define MPARK_TYPE_PACK_ELEMENT\n#endif\n\n#if defined(__cpp_constexpr) && __cpp_constexpr >= 200704 && \\\n !(defined(__GNUC__) && __GNUC__ == 4 && __GNUC_MINOR__ == 9)\n#define MPARK_CPP11_CONSTEXPR\n#endif\n\n#if defined(__cpp_constexpr) && __cpp_constexpr >= 201304\n#define MPARK_CPP14_CONSTEXPR\n#endif\n\n#if __has_feature(cxx_exceptions) || defined(__cpp_exceptions) || \\\n (defined(_MSC_VER) && defined(_CPPUNWIND))\n#define MPARK_EXCEPTIONS\n#endif\n\n#if defined(__cpp_generic_lambdas) || defined(_MSC_VER)\n#define MPARK_GENERIC_LAMBDAS\n#endif\n\n#if defined(__cpp_lib_integer_sequence)\n#define MPARK_INTEGER_SEQUENCE\n#endif\n\n#if (defined(__cpp_decltype_auto) && defined(__cpp_return_type_deduction)) || defined(_MSC_VER)\n#define MPARK_RETURN_TYPE_DEDUCTION\n#endif\n\n#if defined(__cpp_lib_transparent_operators) || defined(_MSC_VER)\n#define MPARK_TRANSPARENT_OPERATORS\n#endif\n\n#if defined(__cpp_variable_templates) || defined(_MSC_VER)\n#define MPARK_VARIABLE_TEMPLATES\n#endif\n\n#if !defined(__GLIBCXX__) || __has_include() // >= libstdc++-5\n#define MPARK_TRIVIALITY_TYPE_TRAITS\n#define MPARK_INCOMPLETE_TYPE_TRAITS\n#endif\n\n#endif // MPARK_CONFIG_HPP\n" }, { "path": "Externals/variant/mpark/in_place.hpp", "content": "// MPark.Variant\n//\n// Copyright Michael Park, 2015-2017\n//\n// Distributed under the Boost Software License, Version 1.0.\n// (See accompanying file LICENSE.md or copy at http://boost.org/LICENSE_1_0.txt)\n\n#ifndef MPARK_IN_PLACE_HPP\n#define MPARK_IN_PLACE_HPP\n\n#include \n\n#include \"config.hpp\"\n\nnamespace mpark {\n\n struct in_place_t { explicit in_place_t() = default; };\n\n template \n struct in_place_index_t { explicit in_place_index_t() = default; };\n\n template \n struct in_place_type_t { explicit in_place_type_t() = default; };\n\n#ifdef MPARK_VARIABLE_TEMPLATES\n constexpr in_place_t in_place{};\n\n template constexpr in_place_index_t in_place_index{};\n\n template constexpr in_place_type_t in_place_type{};\n#endif\n\n} // namespace mpark\n\n#endif // MPARK_IN_PLACE_HPP\n" }, { "path": "Externals/variant/mpark/lib.hpp", "content": "// MPark.Variant\n//\n// Copyright Michael Park, 2015-2017\n//\n// Distributed under the Boost Software License, Version 1.0.\n// (See accompanying file LICENSE.md or copy at http://boost.org/LICENSE_1_0.txt)\n\n#ifndef MPARK_LIB_HPP\n#define MPARK_LIB_HPP\n\n#include \n#include \n#include \n#include \n\n#include \"config.hpp\"\n\n#define MPARK_RETURN(...) \\\n noexcept(noexcept(__VA_ARGS__)) -> decltype(__VA_ARGS__) { return __VA_ARGS__; }\n\nnamespace mpark {\n namespace lib {\n template \n struct identity { using type = T; };\n\n inline namespace cpp14 {\n template \n struct array {\n constexpr const T &operator[](std::size_t index) const {\n return data[index];\n }\n\n T data[N == 0 ? 1 : N];\n };\n\n template \n using add_pointer_t = typename std::add_pointer::type;\n\n template \n using common_type_t = typename std::common_type::type;\n\n template \n using decay_t = typename std::decay::type;\n\n template \n using enable_if_t = typename std::enable_if::type;\n\n template \n using remove_const_t = typename std::remove_const::type;\n\n template \n using remove_reference_t = typename std::remove_reference::type;\n\n template \n using remove_cvref_t =\n typename std::remove_cv>::type;\n\n template \n inline constexpr T &&forward(remove_reference_t &t) noexcept {\n return static_cast(t);\n }\n\n template \n inline constexpr T &&forward(remove_reference_t &&t) noexcept {\n static_assert(!std::is_lvalue_reference::value,\n \"can not forward an rvalue as an lvalue\");\n return static_cast(t);\n }\n\n template \n inline constexpr remove_reference_t &&move(T &&t) noexcept {\n return static_cast &&>(t);\n }\n\n#ifdef MPARK_INTEGER_SEQUENCE\n using std::integer_sequence;\n using std::index_sequence;\n using std::make_index_sequence;\n using std::index_sequence_for;\n#else\n template \n struct integer_sequence {\n using value_type = T;\n static constexpr std::size_t size() noexcept { return sizeof...(Is); }\n };\n\n template \n using index_sequence = integer_sequence;\n\n template \n struct make_index_sequence_concat;\n\n template \n struct make_index_sequence_concat,\n index_sequence>\n : identity> {};\n\n template \n struct make_index_sequence_impl;\n\n template \n using make_index_sequence = typename make_index_sequence_impl::type;\n\n template \n struct make_index_sequence_impl\n : make_index_sequence_concat,\n make_index_sequence> {};\n\n template <>\n struct make_index_sequence_impl<0> : identity> {};\n\n template <>\n struct make_index_sequence_impl<1> : identity> {};\n\n template \n using index_sequence_for = make_index_sequence;\n#endif\n\n // \n#ifdef MPARK_TRANSPARENT_OPERATORS\n using equal_to = std::equal_to<>;\n#else\n struct equal_to {\n template \n inline constexpr auto operator()(Lhs &&lhs, Rhs &&rhs) const\n MPARK_RETURN(lib::forward(lhs) == lib::forward(rhs))\n };\n#endif\n\n#ifdef MPARK_TRANSPARENT_OPERATORS\n using not_equal_to = std::not_equal_to<>;\n#else\n struct not_equal_to {\n template \n inline constexpr auto operator()(Lhs &&lhs, Rhs &&rhs) const\n MPARK_RETURN(lib::forward(lhs) != lib::forward(rhs))\n };\n#endif\n\n#ifdef MPARK_TRANSPARENT_OPERATORS\n using less = std::less<>;\n#else\n struct less {\n template \n inline constexpr auto operator()(Lhs &&lhs, Rhs &&rhs) const\n MPARK_RETURN(lib::forward(lhs) < lib::forward(rhs))\n };\n#endif\n\n#ifdef MPARK_TRANSPARENT_OPERATORS\n using greater = std::greater<>;\n#else\n struct greater {\n template \n inline constexpr auto operator()(Lhs &&lhs, Rhs &&rhs) const\n MPARK_RETURN(lib::forward(lhs) > lib::forward(rhs))\n };\n#endif\n\n#ifdef MPARK_TRANSPARENT_OPERATORS\n using less_equal = std::less_equal<>;\n#else\n struct less_equal {\n template \n inline constexpr auto operator()(Lhs &&lhs, Rhs &&rhs) const\n MPARK_RETURN(lib::forward(lhs) <= lib::forward(rhs))\n };\n#endif\n\n#ifdef MPARK_TRANSPARENT_OPERATORS\n using greater_equal = std::greater_equal<>;\n#else\n struct greater_equal {\n template \n inline constexpr auto operator()(Lhs &&lhs, Rhs &&rhs) const\n MPARK_RETURN(lib::forward(lhs) >= lib::forward(rhs))\n };\n#endif\n } // namespace cpp14\n\n inline namespace cpp17 {\n\n // \n template \n using bool_constant = std::integral_constant;\n\n template \n struct voider : identity {};\n\n template \n using void_t = typename voider::type;\n\n namespace detail {\n namespace swappable {\n\n using std::swap;\n\n template \n struct is_swappable {\n private:\n template (),\n std::declval()))>\n inline static std::true_type test(int);\n\n template \n inline static std::false_type test(...);\n\n public:\n static constexpr bool value = decltype(test(0))::value;\n };\n\n template \n struct is_nothrow_swappable {\n static constexpr bool value =\n noexcept(swap(std::declval(), std::declval()));\n };\n\n template \n struct is_nothrow_swappable : std::false_type {};\n\n } // namespace swappable\n } // namespace detail\n\n using detail::swappable::is_swappable;\n\n template \n using is_nothrow_swappable =\n detail::swappable::is_nothrow_swappable::value, T>;\n\n // \n namespace detail {\n\n template \n struct is_reference_wrapper : std::false_type {};\n\n template \n struct is_reference_wrapper>\n : std::true_type {};\n\n template \n struct Invoke;\n\n template <>\n struct Invoke {\n template \n inline static constexpr auto invoke(R T::*pmf, Arg &&arg, Args &&... args)\n MPARK_RETURN((lib::forward(arg).*pmf)(lib::forward(args)...))\n };\n\n template <>\n struct Invoke {\n template \n inline static constexpr auto invoke(R T::*pmf, Arg &&arg, Args &&... args)\n MPARK_RETURN((lib::forward(arg).get().*pmf)(lib::forward(args)...))\n };\n\n template <>\n struct Invoke {\n template \n inline static constexpr auto invoke(R T::*pmf, Arg &&arg, Args &&... args)\n MPARK_RETURN(((*lib::forward(arg)).*pmf)(lib::forward(args)...))\n };\n\n template <>\n struct Invoke {\n template \n inline static constexpr auto invoke(R T::*pmo, Arg &&arg)\n MPARK_RETURN(lib::forward(arg).*pmo)\n };\n\n template <>\n struct Invoke {\n template \n inline static constexpr auto invoke(R T::*pmo, Arg &&arg)\n MPARK_RETURN(lib::forward(arg).get().*pmo)\n };\n\n template <>\n struct Invoke {\n template \n inline static constexpr auto invoke(R T::*pmo, Arg &&arg)\n MPARK_RETURN((*lib::forward(arg)).*pmo)\n };\n\n template \n inline constexpr auto invoke(R T::*f, Arg &&arg, Args &&... args)\n MPARK_RETURN(\n Invoke::value,\n (std::is_base_of>::value\n ? 0\n : is_reference_wrapper>::value\n ? 1\n : 2)>::invoke(f,\n lib::forward(arg),\n lib::forward(args)...))\n\n#ifdef _MSC_VER\n#pragma warning(push)\n#pragma warning(disable : 4100)\n#endif\n template \n inline constexpr auto invoke(F &&f, Args &&... args)\n MPARK_RETURN(lib::forward(f)(lib::forward(args)...))\n#ifdef _MSC_VER\n#pragma warning(pop)\n#endif\n } // namespace detail\n\n template \n inline constexpr auto invoke(F &&f, Args &&... args)\n MPARK_RETURN(detail::invoke(lib::forward(f),\n lib::forward(args)...))\n\n namespace detail {\n\n template \n struct invoke_result {};\n\n template \n struct invoke_result(), std::declval()...))>,\n F,\n Args...>\n : identity(), std::declval()...))> {};\n\n } // namespace detail\n\n template \n using invoke_result = detail::invoke_result;\n\n template \n using invoke_result_t = typename invoke_result::type;\n\n namespace detail {\n\n template \n struct is_invocable : std::false_type {};\n\n template \n struct is_invocable>, F, Args...>\n : std::true_type {};\n\n template \n struct is_invocable_r : std::false_type {};\n\n template \n struct is_invocable_r>,\n R,\n F,\n Args...>\n : std::is_convertible, R> {};\n\n } // namespace detail\n\n template \n using is_invocable = detail::is_invocable;\n\n template \n using is_invocable_r = detail::is_invocable_r;\n\n // \n#ifdef MPARK_BUILTIN_ADDRESSOF\n template \n inline constexpr T *addressof(T &arg) noexcept {\n return __builtin_addressof(arg);\n }\n#else\n namespace detail {\n\n namespace has_addressof_impl {\n\n struct fail;\n\n template \n inline fail operator&(T &&);\n\n template \n inline static constexpr bool impl() {\n return (std::is_class::value || std::is_union::value) &&\n !std::is_same()), fail>::value;\n }\n\n } // namespace has_addressof_impl\n\n template \n using has_addressof = bool_constant()>;\n\n template \n inline constexpr T *addressof(T &arg, std::true_type) noexcept {\n return std::addressof(arg);\n }\n\n template \n inline constexpr T *addressof(T &arg, std::false_type) noexcept {\n return &arg;\n }\n\n } // namespace detail\n\n template \n inline constexpr T *addressof(T &arg) noexcept {\n return detail::addressof(arg, detail::has_addressof{});\n }\n#endif\n\n template \n inline constexpr T *addressof(const T &&) = delete;\n\n } // namespace cpp17\n\n template \n struct remove_all_extents : identity {};\n\n template \n struct remove_all_extents> : remove_all_extents {};\n\n template \n using remove_all_extents_t = typename remove_all_extents::type;\n\n template \n using size_constant = std::integral_constant;\n\n template \n struct indexed_type : size_constant { using type = T; };\n\n template \n using all = std::is_same,\n integer_sequence>;\n\n#ifdef MPARK_TYPE_PACK_ELEMENT\n template \n using type_pack_element_t = __type_pack_element;\n#else\n template \n struct type_pack_element_impl {\n private:\n template \n struct set;\n\n template \n struct set> : indexed_type... {};\n\n template \n inline static std::enable_if impl(indexed_type);\n\n inline static std::enable_if impl(...);\n\n public:\n using type = decltype(impl(set>{}));\n };\n\n template \n using type_pack_element = typename type_pack_element_impl::type;\n\n template \n using type_pack_element_t = typename type_pack_element::type;\n#endif\n\n#ifdef MPARK_TRIVIALITY_TYPE_TRAITS\n using std::is_trivially_copy_constructible;\n using std::is_trivially_move_constructible;\n using std::is_trivially_copy_assignable;\n using std::is_trivially_move_assignable;\n#else\n template \n struct is_trivially_copy_constructible\n : bool_constant<\n std::is_copy_constructible::value && __has_trivial_copy(T)> {};\n\n template \n struct is_trivially_move_constructible : bool_constant<__is_trivial(T)> {};\n\n template \n struct is_trivially_copy_assignable\n : bool_constant<\n std::is_copy_assignable::value && __has_trivial_assign(T)> {};\n\n template \n struct is_trivially_move_assignable : bool_constant<__is_trivial(T)> {};\n#endif\n\n template \n struct dependent_type : T {};\n\n template \n struct push_back;\n\n template \n using push_back_t = typename push_back::type;\n\n template \n struct push_back, J> {\n using type = index_sequence;\n };\n\n } // namespace lib\n} // namespace mpark\n\n#undef MPARK_RETURN\n\n#endif // MPARK_LIB_HPP\n" }, { "path": "Externals/variant/mpark/variant.hpp", "content": "// MPark.Variant\n//\n// Copyright Michael Park, 2015-2017\n//\n// Distributed under the Boost Software License, Version 1.0.\n// (See accompanying file LICENSE.md or copy at http://boost.org/LICENSE_1_0.txt)\n\n#ifndef MPARK_VARIANT_HPP\n#define MPARK_VARIANT_HPP\n\n/*\n variant synopsis\n\nnamespace std {\n\n // 20.7.2, class template variant\n template \n class variant {\n public:\n\n // 20.7.2.1, constructors\n constexpr variant() noexcept(see below);\n variant(const variant&);\n variant(variant&&) noexcept(see below);\n\n template constexpr variant(T&&) noexcept(see below);\n\n template \n constexpr explicit variant(in_place_type_t, Args&&...);\n\n template \n constexpr explicit variant(\n in_place_type_t, initializer_list, Args&&...);\n\n template \n constexpr explicit variant(in_place_index_t, Args&&...);\n\n template \n constexpr explicit variant(\n in_place_index_t, initializer_list, Args&&...);\n\n // 20.7.2.2, destructor\n ~variant();\n\n // 20.7.2.3, assignment\n variant& operator=(const variant&);\n variant& operator=(variant&&) noexcept(see below);\n\n template variant& operator=(T&&) noexcept(see below);\n\n // 20.7.2.4, modifiers\n template \n T& emplace(Args&&...);\n\n template \n T& emplace(initializer_list, Args&&...);\n\n template \n variant_alternative& emplace(Args&&...);\n\n template \n variant_alternative& emplace(initializer_list, Args&&...);\n\n // 20.7.2.5, value status\n constexpr bool valueless_by_exception() const noexcept;\n constexpr size_t index() const noexcept;\n\n // 20.7.2.6, swap\n void swap(variant&) noexcept(see below);\n };\n\n // 20.7.3, variant helper classes\n template struct variant_size; // undefined\n\n template \n constexpr size_t variant_size_v = variant_size::value;\n\n template struct variant_size;\n template struct variant_size;\n template struct variant_size;\n\n template \n struct variant_size>;\n\n template struct variant_alternative; // undefined\n\n template \n using variant_alternative_t = typename variant_alternative::type;\n\n template struct variant_alternative;\n template struct variant_alternative;\n template struct variant_alternative;\n\n template \n struct variant_alternative>;\n\n constexpr size_t variant_npos = -1;\n\n // 20.7.4, value access\n template \n constexpr bool holds_alternative(const variant&) noexcept;\n\n template \n constexpr variant_alternative_t>&\n get(variant&);\n\n template \n constexpr variant_alternative_t>&&\n get(variant&&);\n\n template \n constexpr variant_alternative_t> const&\n get(const variant&);\n\n template \n constexpr variant_alternative_t> const&&\n get(const variant&&);\n\n template \n constexpr T& get(variant&);\n\n template \n constexpr T&& get(variant&&);\n\n template \n constexpr const T& get(const variant&);\n\n template \n constexpr const T&& get(const variant&&);\n\n template \n constexpr add_pointer_t>>\n get_if(variant*) noexcept;\n\n template \n constexpr add_pointer_t>>\n get_if(const variant*) noexcept;\n\n template \n constexpr add_pointer_t\n get_if(variant*) noexcept;\n\n template \n constexpr add_pointer_t\n get_if(const variant*) noexcept;\n\n // 20.7.5, relational operators\n template \n constexpr bool operator==(const variant&, const variant&);\n\n template \n constexpr bool operator!=(const variant&, const variant&);\n\n template \n constexpr bool operator<(const variant&, const variant&);\n\n template \n constexpr bool operator>(const variant&, const variant&);\n\n template \n constexpr bool operator<=(const variant&, const variant&);\n\n template \n constexpr bool operator>=(const variant&, const variant&);\n\n // 20.7.6, visitation\n template \n constexpr see below visit(Visitor&&, Variants&&...);\n\n // 20.7.7, class monostate\n struct monostate;\n\n // 20.7.8, monostate relational operators\n constexpr bool operator<(monostate, monostate) noexcept;\n constexpr bool operator>(monostate, monostate) noexcept;\n constexpr bool operator<=(monostate, monostate) noexcept;\n constexpr bool operator>=(monostate, monostate) noexcept;\n constexpr bool operator==(monostate, monostate) noexcept;\n constexpr bool operator!=(monostate, monostate) noexcept;\n\n // 20.7.9, specialized algorithms\n template \n void swap(variant&, variant&) noexcept(see below);\n\n // 20.7.10, class bad_variant_access\n class bad_variant_access;\n\n // 20.7.11, hash support\n template struct hash;\n template struct hash>;\n template <> struct hash;\n\n} // namespace std\n\n*/\n\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n\n#include \"config.hpp\"\n#include \"in_place.hpp\"\n#include \"lib.hpp\"\n\nnamespace mpark {\n\n#ifdef MPARK_RETURN_TYPE_DEDUCTION\n\n#define AUTO auto\n#define AUTO_RETURN(...) { return __VA_ARGS__; }\n\n#define AUTO_REFREF auto &&\n#define AUTO_REFREF_RETURN(...) { return __VA_ARGS__; }\n\n#define DECLTYPE_AUTO decltype(auto)\n#define DECLTYPE_AUTO_RETURN(...) { return __VA_ARGS__; }\n\n#else\n\n#define AUTO auto\n#define AUTO_RETURN(...) \\\n -> lib::decay_t { return __VA_ARGS__; }\n\n#define AUTO_REFREF auto\n#define AUTO_REFREF_RETURN(...) \\\n -> decltype((__VA_ARGS__)) { \\\n static_assert(std::is_reference::value, \"\"); \\\n return __VA_ARGS__; \\\n }\n\n#define DECLTYPE_AUTO auto\n#define DECLTYPE_AUTO_RETURN(...) \\\n -> decltype(__VA_ARGS__) { return __VA_ARGS__; }\n\n#endif\n\n class bad_variant_access : public std::exception {\n public:\n virtual const char *what() const noexcept override { return \"bad_variant_access\"; }\n };\n\n [[noreturn]] inline void throw_bad_variant_access() {\n#ifdef MPARK_EXCEPTIONS\n throw bad_variant_access{};\n#else\n std::terminate();\n MPARK_BUILTIN_UNREACHABLE;\n#endif\n }\n\n template \n class variant;\n\n template \n struct variant_size;\n\n#ifdef MPARK_VARIABLE_TEMPLATES\n template \n constexpr std::size_t variant_size_v = variant_size::value;\n#endif\n\n template \n struct variant_size : variant_size {};\n\n template \n struct variant_size : variant_size {};\n\n template \n struct variant_size : variant_size {};\n\n template \n struct variant_size> : lib::size_constant {};\n\n template \n struct variant_alternative;\n\n template \n using variant_alternative_t = typename variant_alternative::type;\n\n template \n struct variant_alternative\n : std::add_const> {};\n\n template \n struct variant_alternative\n : std::add_volatile> {};\n\n template \n struct variant_alternative\n : std::add_cv> {};\n\n template \n struct variant_alternative> {\n static_assert(I < sizeof...(Ts),\n \"index out of bounds in `std::variant_alternative<>`\");\n using type = lib::type_pack_element_t;\n };\n\n constexpr std::size_t variant_npos = static_cast(-1);\n\n namespace detail {\n\n constexpr std::size_t not_found = static_cast(-1);\n constexpr std::size_t ambiguous = static_cast(-2);\n\n#ifdef MPARK_CPP14_CONSTEXPR\n template \n inline constexpr std::size_t find_index() {\n constexpr lib::array matches = {\n {std::is_same::value...}\n };\n std::size_t result = not_found;\n for (std::size_t i = 0; i < sizeof...(Ts); ++i) {\n if (matches[i]) {\n if (result != not_found) {\n return ambiguous;\n }\n result = i;\n }\n }\n return result;\n }\n#else\n inline constexpr std::size_t find_index_impl(std::size_t result,\n std::size_t) {\n return result;\n }\n\n template \n inline constexpr std::size_t find_index_impl(std::size_t result,\n std::size_t idx,\n bool b,\n Bs... bs) {\n return b ? (result != not_found ? ambiguous\n : find_index_impl(idx, idx + 1, bs...))\n : find_index_impl(result, idx + 1, bs...);\n }\n\n template \n inline constexpr std::size_t find_index() {\n return find_index_impl(not_found, 0, std::is_same::value...);\n }\n#endif\n\n template \n using find_index_sfinae_impl =\n lib::enable_if_t>;\n\n template \n using find_index_sfinae = find_index_sfinae_impl()>;\n\n template \n struct find_index_checked_impl : lib::size_constant {\n static_assert(I != not_found, \"the specified type is not found.\");\n static_assert(I != ambiguous, \"the specified type is ambiguous.\");\n };\n\n template \n using find_index_checked = find_index_checked_impl()>;\n\n struct valueless_t {};\n\n enum class Trait { TriviallyAvailable, Available, Unavailable };\n\n template class IsTriviallyAvailable,\n template class IsAvailable>\n inline constexpr Trait trait() {\n return IsTriviallyAvailable::value\n ? Trait::TriviallyAvailable\n : IsAvailable::value ? Trait::Available\n : Trait::Unavailable;\n }\n\n#ifdef MPARK_CPP14_CONSTEXPR\n template \n inline constexpr Trait common_trait(Traits... traits_) {\n Trait result = Trait::TriviallyAvailable;\n lib::array traits = {{traits_...}};\n for (std::size_t i = 0; i < sizeof...(Traits); ++i) {\n Trait t = traits[i];\n if (static_cast(t) > static_cast(result)) {\n result = t;\n }\n }\n return result;\n }\n#else\n inline constexpr Trait common_trait_impl(Trait result) { return result; }\n\n template \n inline constexpr Trait common_trait_impl(Trait result,\n Trait t,\n Traits... ts) {\n return static_cast(t) > static_cast(result)\n ? common_trait_impl(t, ts...)\n : common_trait_impl(result, ts...);\n }\n\n template \n inline constexpr Trait common_trait(Traits... ts) {\n return common_trait_impl(Trait::TriviallyAvailable, ts...);\n }\n#endif\n\n template \n struct traits {\n static constexpr Trait copy_constructible_trait =\n common_trait(trait()...);\n\n static constexpr Trait move_constructible_trait =\n common_trait(trait()...);\n\n static constexpr Trait copy_assignable_trait =\n common_trait(copy_constructible_trait,\n trait()...);\n\n static constexpr Trait move_assignable_trait =\n common_trait(move_constructible_trait,\n trait()...);\n\n static constexpr Trait destructible_trait =\n common_trait(trait()...);\n };\n\n namespace access {\n\n struct recursive_union {\n#ifdef MPARK_RETURN_TYPE_DEDUCTION\n template \n inline static constexpr auto &&get_alt(V &&v, in_place_index_t<0>) {\n return lib::forward(v).head_;\n }\n\n template \n inline static constexpr auto &&get_alt(V &&v, in_place_index_t) {\n return get_alt(lib::forward(v).tail_, in_place_index_t{});\n }\n#else\n template \n struct get_alt_impl {\n template \n inline constexpr AUTO_REFREF operator()(V &&v) const\n AUTO_REFREF_RETURN(get_alt_impl{}(lib::forward(v).tail_))\n };\n\n template \n struct get_alt_impl<0, Dummy> {\n template \n inline constexpr AUTO_REFREF operator()(V &&v) const\n AUTO_REFREF_RETURN(lib::forward(v).head_)\n };\n\n template \n inline static constexpr AUTO_REFREF get_alt(V &&v, in_place_index_t)\n AUTO_REFREF_RETURN(get_alt_impl{}(lib::forward(v)))\n#endif\n };\n\n struct base {\n template \n inline static constexpr AUTO_REFREF get_alt(V &&v)\n#ifdef _MSC_VER\n AUTO_REFREF_RETURN(recursive_union::get_alt(\n lib::forward(v).data_, in_place_index_t{}))\n#else\n AUTO_REFREF_RETURN(recursive_union::get_alt(\n data(lib::forward(v)), in_place_index_t{}))\n#endif\n };\n\n struct variant {\n template \n inline static constexpr AUTO_REFREF get_alt(V &&v)\n AUTO_REFREF_RETURN(base::get_alt(lib::forward(v).impl_))\n };\n\n } // namespace access\n\n namespace visitation {\n\n#if defined(MPARK_CPP14_CONSTEXPR) && !defined(_MSC_VER)\n#define MPARK_VARIANT_SWITCH_VISIT\n#endif\n\n struct base {\n template \n using dispatch_result_t = decltype(\n lib::invoke(std::declval(),\n access::base::get_alt<0>(std::declval())...));\n\n template \n struct expected {\n template \n inline static constexpr bool but_got() {\n return std::is_same::value;\n }\n };\n\n template \n struct visit_return_type_check {\n static_assert(\n expected::template but_got(),\n \"`visit` requires the visitor to have a single return type\");\n\n template \n inline static constexpr DECLTYPE_AUTO invoke(Visitor &&visitor,\n Alts &&... alts)\n DECLTYPE_AUTO_RETURN(lib::invoke(lib::forward(visitor),\n lib::forward(alts)...))\n };\n\n#ifdef MPARK_VARIANT_SWITCH_VISIT\n template \n struct dispatcher;\n\n template \n struct dispatcher {\n template \n MPARK_ALWAYS_INLINE static constexpr R dispatch(\n F &&, typename ITs::type &&..., Vs &&...) {\n MPARK_BUILTIN_UNREACHABLE;\n }\n\n template \n MPARK_ALWAYS_INLINE static constexpr R dispatch_case(F &&, Vs &&...) {\n MPARK_BUILTIN_UNREACHABLE;\n }\n\n template \n MPARK_ALWAYS_INLINE static constexpr R dispatch_at(std::size_t,\n F &&,\n Vs &&...) {\n MPARK_BUILTIN_UNREACHABLE;\n }\n };\n\n template \n struct dispatcher {\n template \n MPARK_ALWAYS_INLINE static constexpr R dispatch(\n F &&f, typename ITs::type &&... visited_vs) {\n using Expected = R;\n using Actual = decltype(lib::invoke(\n lib::forward(f),\n access::base::get_alt(\n lib::forward(visited_vs))...));\n return visit_return_type_check::invoke(\n lib::forward(f),\n access::base::get_alt(\n lib::forward(visited_vs))...);\n }\n\n template \n MPARK_ALWAYS_INLINE static constexpr R dispatch(\n F &&f, typename ITs::type &&... visited_vs, V &&v, Vs &&... vs) {\n#define MPARK_DISPATCH(I) \\\n dispatcher<(I < lib::decay_t::size()), \\\n R, \\\n ITs..., \\\n lib::indexed_type>:: \\\n template dispatch<0>(lib::forward(f), \\\n lib::forward(visited_vs)..., \\\n lib::forward(v), \\\n lib::forward(vs)...)\n\n#define MPARK_DEFAULT(I) \\\n dispatcher<(I < lib::decay_t::size()), R, ITs...>::template dispatch( \\\n lib::forward(f), \\\n lib::forward(visited_vs)..., \\\n lib::forward(v), \\\n lib::forward(vs)...)\n\n switch (v.index()) {\n case B + 0: return MPARK_DISPATCH(B + 0);\n case B + 1: return MPARK_DISPATCH(B + 1);\n case B + 2: return MPARK_DISPATCH(B + 2);\n case B + 3: return MPARK_DISPATCH(B + 3);\n case B + 4: return MPARK_DISPATCH(B + 4);\n case B + 5: return MPARK_DISPATCH(B + 5);\n case B + 6: return MPARK_DISPATCH(B + 6);\n case B + 7: return MPARK_DISPATCH(B + 7);\n case B + 8: return MPARK_DISPATCH(B + 8);\n case B + 9: return MPARK_DISPATCH(B + 9);\n case B + 10: return MPARK_DISPATCH(B + 10);\n case B + 11: return MPARK_DISPATCH(B + 11);\n case B + 12: return MPARK_DISPATCH(B + 12);\n case B + 13: return MPARK_DISPATCH(B + 13);\n case B + 14: return MPARK_DISPATCH(B + 14);\n case B + 15: return MPARK_DISPATCH(B + 15);\n case B + 16: return MPARK_DISPATCH(B + 16);\n case B + 17: return MPARK_DISPATCH(B + 17);\n case B + 18: return MPARK_DISPATCH(B + 18);\n case B + 19: return MPARK_DISPATCH(B + 19);\n case B + 20: return MPARK_DISPATCH(B + 20);\n case B + 21: return MPARK_DISPATCH(B + 21);\n case B + 22: return MPARK_DISPATCH(B + 22);\n case B + 23: return MPARK_DISPATCH(B + 23);\n case B + 24: return MPARK_DISPATCH(B + 24);\n case B + 25: return MPARK_DISPATCH(B + 25);\n case B + 26: return MPARK_DISPATCH(B + 26);\n case B + 27: return MPARK_DISPATCH(B + 27);\n case B + 28: return MPARK_DISPATCH(B + 28);\n case B + 29: return MPARK_DISPATCH(B + 29);\n case B + 30: return MPARK_DISPATCH(B + 30);\n case B + 31: return MPARK_DISPATCH(B + 31);\n default: return MPARK_DEFAULT(B + 32);\n }\n\n#undef MPARK_DEFAULT\n#undef MPARK_DISPATCH\n }\n\n template \n MPARK_ALWAYS_INLINE static constexpr R dispatch_case(F &&f,\n Vs &&... vs) {\n using Expected = R;\n using Actual = decltype(\n lib::invoke(lib::forward(f),\n access::base::get_alt(lib::forward(vs))...));\n return visit_return_type_check::invoke(\n lib::forward(f),\n access::base::get_alt(lib::forward(vs))...);\n }\n\n template \n MPARK_ALWAYS_INLINE static constexpr R dispatch_at(std::size_t index,\n F &&f,\n V &&v,\n Vs &&... vs) {\n static_assert(lib::all<(lib::decay_t::size() ==\n lib::decay_t::size())...>::value,\n \"all of the variants must be the same size.\");\n#define MPARK_DISPATCH_AT(I) \\\n dispatcher<(I < lib::decay_t::size()), R>::template dispatch_case( \\\n lib::forward(f), lib::forward(v), lib::forward(vs)...)\n\n#define MPARK_DEFAULT(I) \\\n dispatcher<(I < lib::decay_t::size()), R>::template dispatch_at( \\\n index, lib::forward(f), lib::forward(v), lib::forward(vs)...)\n\n switch (index) {\n case B + 0: return MPARK_DISPATCH_AT(B + 0);\n case B + 1: return MPARK_DISPATCH_AT(B + 1);\n case B + 2: return MPARK_DISPATCH_AT(B + 2);\n case B + 3: return MPARK_DISPATCH_AT(B + 3);\n case B + 4: return MPARK_DISPATCH_AT(B + 4);\n case B + 5: return MPARK_DISPATCH_AT(B + 5);\n case B + 6: return MPARK_DISPATCH_AT(B + 6);\n case B + 7: return MPARK_DISPATCH_AT(B + 7);\n case B + 8: return MPARK_DISPATCH_AT(B + 8);\n case B + 9: return MPARK_DISPATCH_AT(B + 9);\n case B + 10: return MPARK_DISPATCH_AT(B + 10);\n case B + 11: return MPARK_DISPATCH_AT(B + 11);\n case B + 12: return MPARK_DISPATCH_AT(B + 12);\n case B + 13: return MPARK_DISPATCH_AT(B + 13);\n case B + 14: return MPARK_DISPATCH_AT(B + 14);\n case B + 15: return MPARK_DISPATCH_AT(B + 15);\n case B + 16: return MPARK_DISPATCH_AT(B + 16);\n case B + 17: return MPARK_DISPATCH_AT(B + 17);\n case B + 18: return MPARK_DISPATCH_AT(B + 18);\n case B + 19: return MPARK_DISPATCH_AT(B + 19);\n case B + 20: return MPARK_DISPATCH_AT(B + 20);\n case B + 21: return MPARK_DISPATCH_AT(B + 21);\n case B + 22: return MPARK_DISPATCH_AT(B + 22);\n case B + 23: return MPARK_DISPATCH_AT(B + 23);\n case B + 24: return MPARK_DISPATCH_AT(B + 24);\n case B + 25: return MPARK_DISPATCH_AT(B + 25);\n case B + 26: return MPARK_DISPATCH_AT(B + 26);\n case B + 27: return MPARK_DISPATCH_AT(B + 27);\n case B + 28: return MPARK_DISPATCH_AT(B + 28);\n case B + 29: return MPARK_DISPATCH_AT(B + 29);\n case B + 30: return MPARK_DISPATCH_AT(B + 30);\n case B + 31: return MPARK_DISPATCH_AT(B + 31);\n default: return MPARK_DEFAULT(B + 32);\n }\n\n#undef MPARK_DEFAULT\n#undef MPARK_DISPATCH_AT\n }\n };\n#else\n template \n inline static constexpr const T &at(const T &elem) noexcept {\n return elem;\n }\n\n template \n inline static constexpr const lib::remove_all_extents_t &at(\n const lib::array &elems, std::size_t i, Is... is) noexcept {\n return at(elems[i], is...);\n }\n\n template \n inline static constexpr lib::array, sizeof...(Fs) + 1>\n make_farray(F &&f, Fs &&... fs) {\n return {{lib::forward(f), lib::forward(fs)...}};\n }\n\n template \n struct make_fmatrix_impl {\n\n template \n inline static constexpr dispatch_result_t dispatch(\n F &&f, Vs &&... vs) {\n using Expected = dispatch_result_t;\n using Actual = decltype(lib::invoke(\n lib::forward(f),\n access::base::get_alt(lib::forward(vs))...));\n return visit_return_type_check::invoke(\n lib::forward(f),\n access::base::get_alt(lib::forward(vs))...);\n }\n\n#ifdef MPARK_RETURN_TYPE_DEDUCTION\n template \n inline static constexpr auto impl(lib::index_sequence) {\n return &dispatch;\n }\n\n template \n inline static constexpr auto impl(Is,\n lib::index_sequence,\n Ls... ls) {\n return make_farray(impl(lib::push_back_t{}, ls...)...);\n }\n#else\n template \n struct impl;\n\n template \n struct impl> {\n inline constexpr AUTO operator()() const\n AUTO_RETURN(&dispatch)\n };\n\n template \n struct impl, Ls...> {\n inline constexpr AUTO operator()() const\n AUTO_RETURN(\n make_farray(impl, Ls...>{}()...))\n };\n#endif\n };\n\n#ifdef MPARK_RETURN_TYPE_DEDUCTION\n template \n inline static constexpr auto make_fmatrix() {\n return make_fmatrix_impl::impl(\n lib::index_sequence<>{},\n lib::make_index_sequence::size()>{}...);\n }\n#else\n template \n inline static constexpr AUTO make_fmatrix()\n AUTO_RETURN(\n typename make_fmatrix_impl::template impl<\n lib::index_sequence<>,\n lib::make_index_sequence::size()>...>{}())\n#endif\n\n template \n struct make_fdiagonal_impl {\n template \n inline static constexpr dispatch_result_t dispatch(\n F &&f, Vs &&... vs) {\n using Expected = dispatch_result_t;\n using Actual = decltype(\n lib::invoke(lib::forward(f),\n access::base::get_alt(lib::forward(vs))...));\n return visit_return_type_check::invoke(\n lib::forward(f),\n access::base::get_alt(lib::forward(vs))...);\n }\n\n template \n inline static constexpr AUTO impl(lib::index_sequence)\n AUTO_RETURN(make_farray(&dispatch...))\n };\n\n template \n inline static constexpr auto make_fdiagonal()\n -> decltype(make_fdiagonal_impl::impl(\n lib::make_index_sequence::size()>{})) {\n static_assert(lib::all<(lib::decay_t::size() ==\n lib::decay_t::size())...>::value,\n \"all of the variants must be the same size.\");\n return make_fdiagonal_impl::impl(\n lib::make_index_sequence::size()>{});\n }\n#endif\n };\n\n#if !defined(MPARK_VARIANT_SWITCH_VISIT) && \\\n (!defined(_MSC_VER) || _MSC_VER >= 1910)\n template \n using fmatrix_t = decltype(base::make_fmatrix());\n\n template \n struct fmatrix {\n static constexpr fmatrix_t value =\n base::make_fmatrix();\n };\n\n template \n constexpr fmatrix_t fmatrix::value;\n\n template \n using fdiagonal_t = decltype(base::make_fdiagonal());\n\n template \n struct fdiagonal {\n static constexpr fdiagonal_t value =\n base::make_fdiagonal();\n };\n\n template \n constexpr fdiagonal_t fdiagonal::value;\n#endif\n\n struct alt {\n template \n inline static constexpr DECLTYPE_AUTO visit_alt(Visitor &&visitor,\n Vs &&... vs)\n#ifdef MPARK_VARIANT_SWITCH_VISIT\n DECLTYPE_AUTO_RETURN(\n base::dispatcher<\n true,\n base::dispatch_result_t(vs)))...>>::\n template dispatch<0>(lib::forward(visitor),\n as_base(lib::forward(vs))...))\n#elif !defined(_MSC_VER) || _MSC_VER >= 1910\n DECLTYPE_AUTO_RETURN(base::at(\n fmatrix(vs)))...>::value,\n vs.index()...)(lib::forward(visitor),\n as_base(lib::forward(vs))...))\n#else\n DECLTYPE_AUTO_RETURN(base::at(\n base::make_fmatrix(vs)))...>(),\n vs.index()...)(lib::forward(visitor),\n as_base(lib::forward(vs))...))\n#endif\n\n template \n inline static constexpr DECLTYPE_AUTO visit_alt_at(std::size_t index,\n Visitor &&visitor,\n Vs &&... vs)\n#ifdef MPARK_VARIANT_SWITCH_VISIT\n DECLTYPE_AUTO_RETURN(\n base::dispatcher<\n true,\n base::dispatch_result_t(vs)))...>>::\n template dispatch_at<0>(index,\n lib::forward(visitor),\n as_base(lib::forward(vs))...))\n#elif !defined(_MSC_VER) || _MSC_VER >= 1910\n DECLTYPE_AUTO_RETURN(base::at(\n fdiagonal(vs)))...>::value,\n index)(lib::forward(visitor),\n as_base(lib::forward(vs))...))\n#else\n DECLTYPE_AUTO_RETURN(base::at(\n base::make_fdiagonal(vs)))...>(),\n index)(lib::forward(visitor),\n as_base(lib::forward(vs))...))\n#endif\n };\n\n struct variant {\n private:\n template \n struct visitor {\n template \n inline static constexpr bool does_not_handle() {\n return lib::is_invocable::value;\n }\n };\n\n template \n struct visit_exhaustiveness_check {\n static_assert(visitor::template does_not_handle(),\n \"`visit` requires the visitor to be exhaustive.\");\n\n inline static constexpr DECLTYPE_AUTO invoke(Visitor &&visitor,\n Values &&... values)\n DECLTYPE_AUTO_RETURN(lib::invoke(lib::forward(visitor),\n lib::forward(values)...))\n };\n\n template \n struct value_visitor {\n Visitor &&visitor_;\n\n template \n inline constexpr DECLTYPE_AUTO operator()(Alts &&... alts) const\n DECLTYPE_AUTO_RETURN(\n visit_exhaustiveness_check<\n Visitor,\n decltype((lib::forward(alts).value))...>::\n invoke(lib::forward(visitor_),\n lib::forward(alts).value...))\n };\n\n template \n inline static constexpr AUTO make_value_visitor(Visitor &&visitor)\n AUTO_RETURN(value_visitor{lib::forward(visitor)})\n\n public:\n template \n inline static constexpr DECLTYPE_AUTO visit_alt(Visitor &&visitor,\n Vs &&... vs)\n DECLTYPE_AUTO_RETURN(alt::visit_alt(lib::forward(visitor),\n lib::forward(vs).impl_...))\n\n template \n inline static constexpr DECLTYPE_AUTO visit_alt_at(std::size_t index,\n Visitor &&visitor,\n Vs &&... vs)\n DECLTYPE_AUTO_RETURN(\n alt::visit_alt_at(index,\n lib::forward(visitor),\n lib::forward(vs).impl_...))\n\n template \n inline static constexpr DECLTYPE_AUTO visit_value(Visitor &&visitor,\n Vs &&... vs)\n DECLTYPE_AUTO_RETURN(\n visit_alt(make_value_visitor(lib::forward(visitor)),\n lib::forward(vs)...))\n\n template \n inline static constexpr DECLTYPE_AUTO visit_value_at(std::size_t index,\n Visitor &&visitor,\n Vs &&... vs)\n DECLTYPE_AUTO_RETURN(\n visit_alt_at(index,\n make_value_visitor(lib::forward(visitor)),\n lib::forward(vs)...))\n };\n\n } // namespace visitation\n\n template \n struct alt {\n using value_type = T;\n\n#ifdef _MSC_VER\n#pragma warning(push)\n#pragma warning(disable : 4244)\n#endif\n template \n inline explicit constexpr alt(in_place_t, Args &&... args)\n : value(lib::forward(args)...) {}\n#ifdef _MSC_VER\n#pragma warning(pop)\n#endif\n\n T value;\n };\n\n template \n union recursive_union;\n\n template \n union recursive_union {};\n\n#define MPARK_VARIANT_RECURSIVE_UNION(destructible_trait, destructor) \\\n template \\\n union recursive_union { \\\n public: \\\n inline explicit constexpr recursive_union(valueless_t) noexcept \\\n : dummy_{} {} \\\n \\\n template \\\n inline explicit constexpr recursive_union(in_place_index_t<0>, \\\n Args &&... args) \\\n : head_(in_place_t{}, lib::forward(args)...) {} \\\n \\\n template \\\n inline explicit constexpr recursive_union(in_place_index_t, \\\n Args &&... args) \\\n : tail_(in_place_index_t{}, lib::forward(args)...) {} \\\n \\\n recursive_union(const recursive_union &) = default; \\\n recursive_union(recursive_union &&) = default; \\\n \\\n destructor \\\n \\\n recursive_union &operator=(const recursive_union &) = default; \\\n recursive_union &operator=(recursive_union &&) = default; \\\n \\\n private: \\\n char dummy_; \\\n alt head_; \\\n recursive_union tail_; \\\n \\\n friend struct access::recursive_union; \\\n }\n\n MPARK_VARIANT_RECURSIVE_UNION(Trait::TriviallyAvailable,\n ~recursive_union() = default;);\n MPARK_VARIANT_RECURSIVE_UNION(Trait::Available,\n ~recursive_union() {});\n MPARK_VARIANT_RECURSIVE_UNION(Trait::Unavailable,\n ~recursive_union() = delete;);\n\n#undef MPARK_VARIANT_RECURSIVE_UNION\n\n template \n using index_t = typename std::conditional<\n sizeof...(Ts) < (std::numeric_limits::max)(),\n unsigned char,\n typename std::conditional<\n sizeof...(Ts) < (std::numeric_limits::max)(),\n unsigned short,\n unsigned int>::type\n >::type;\n\n template \n class base {\n public:\n inline explicit constexpr base(valueless_t tag) noexcept\n : data_(tag), index_(static_cast>(-1)) {}\n\n template \n inline explicit constexpr base(in_place_index_t, Args &&... args)\n : data_(in_place_index_t{}, lib::forward(args)...),\n index_(I) {}\n\n inline constexpr bool valueless_by_exception() const noexcept {\n return index_ == static_cast>(-1);\n }\n\n inline constexpr std::size_t index() const noexcept {\n return valueless_by_exception() ? variant_npos : index_;\n }\n\n protected:\n using data_t = recursive_union;\n\n friend inline constexpr base &as_base(base &b) { return b; }\n friend inline constexpr const base &as_base(const base &b) { return b; }\n friend inline constexpr base &&as_base(base &&b) { return lib::move(b); }\n friend inline constexpr const base &&as_base(const base &&b) { return lib::move(b); }\n\n friend inline constexpr data_t &data(base &b) { return b.data_; }\n friend inline constexpr const data_t &data(const base &b) { return b.data_; }\n friend inline constexpr data_t &&data(base &&b) { return lib::move(b).data_; }\n friend inline constexpr const data_t &&data(const base &&b) { return lib::move(b).data_; }\n\n inline static constexpr std::size_t size() { return sizeof...(Ts); }\n\n data_t data_;\n index_t index_;\n\n friend struct access::base;\n friend struct visitation::base;\n };\n\n struct dtor {\n#ifdef _MSC_VER\n#pragma warning(push)\n#pragma warning(disable : 4100)\n#endif\n template \n inline void operator()(Alt &alt) const noexcept { alt.~Alt(); }\n#ifdef _MSC_VER\n#pragma warning(pop)\n#endif\n };\n\n#if !defined(_MSC_VER) || _MSC_VER >= 1910\n#define MPARK_INHERITING_CTOR(type, base) using base::base;\n#else\n#define MPARK_INHERITING_CTOR(type, base) \\\n template \\\n inline explicit constexpr type(Args &&... args) \\\n : base(lib::forward(args)...) {}\n#endif\n\n template \n class destructor;\n\n#define MPARK_VARIANT_DESTRUCTOR(destructible_trait, definition, destroy) \\\n template \\\n class destructor, destructible_trait> \\\n : public base { \\\n using super = base; \\\n \\\n public: \\\n MPARK_INHERITING_CTOR(destructor, super) \\\n using super::operator=; \\\n \\\n destructor(const destructor &) = default; \\\n destructor(destructor &&) = default; \\\n definition \\\n destructor &operator=(const destructor &) = default; \\\n destructor &operator=(destructor &&) = default; \\\n \\\n protected: \\\n destroy \\\n }\n\n MPARK_VARIANT_DESTRUCTOR(\n Trait::TriviallyAvailable,\n ~destructor() = default;,\n inline void destroy() noexcept {\n this->index_ = static_cast>(-1);\n });\n\n MPARK_VARIANT_DESTRUCTOR(\n Trait::Available,\n ~destructor() { destroy(); },\n inline void destroy() noexcept {\n if (!this->valueless_by_exception()) {\n visitation::alt::visit_alt(dtor{}, *this);\n }\n this->index_ = static_cast>(-1);\n });\n\n MPARK_VARIANT_DESTRUCTOR(\n Trait::Unavailable,\n ~destructor() = delete;,\n inline void destroy() noexcept = delete;);\n\n#undef MPARK_VARIANT_DESTRUCTOR\n\n template \n class constructor : public destructor {\n using super = destructor;\n\n public:\n MPARK_INHERITING_CTOR(constructor, super)\n using super::operator=;\n\n protected:\n#ifndef MPARK_GENERIC_LAMBDAS\n struct ctor {\n template \n inline void operator()(LhsAlt &lhs_alt, RhsAlt &&rhs_alt) const {\n constructor::construct_alt(lhs_alt,\n lib::forward(rhs_alt).value);\n }\n };\n#endif\n\n template \n inline static T &construct_alt(alt &a, Args &&... args) {\n auto *result = ::new (static_cast(lib::addressof(a)))\n alt(in_place_t{}, lib::forward(args)...);\n return result->value;\n }\n\n template \n inline static void generic_construct(constructor &lhs, Rhs &&rhs) {\n lhs.destroy();\n if (!rhs.valueless_by_exception()) {\n visitation::alt::visit_alt_at(\n rhs.index(),\n#ifdef MPARK_GENERIC_LAMBDAS\n [](auto &lhs_alt, auto &&rhs_alt) {\n constructor::construct_alt(\n lhs_alt, lib::forward(rhs_alt).value);\n }\n#else\n ctor{}\n#endif\n ,\n lhs,\n lib::forward(rhs));\n lhs.index_ = rhs.index_;\n }\n }\n };\n\n template \n class move_constructor;\n\n#define MPARK_VARIANT_MOVE_CONSTRUCTOR(move_constructible_trait, definition) \\\n template \\\n class move_constructor, move_constructible_trait> \\\n : public constructor> { \\\n using super = constructor>; \\\n \\\n public: \\\n MPARK_INHERITING_CTOR(move_constructor, super) \\\n using super::operator=; \\\n \\\n move_constructor(const move_constructor &) = default; \\\n definition \\\n ~move_constructor() = default; \\\n move_constructor &operator=(const move_constructor &) = default; \\\n move_constructor &operator=(move_constructor &&) = default; \\\n }\n\n MPARK_VARIANT_MOVE_CONSTRUCTOR(\n Trait::TriviallyAvailable,\n move_constructor(move_constructor &&that) = default;);\n\n MPARK_VARIANT_MOVE_CONSTRUCTOR(\n Trait::Available,\n move_constructor(move_constructor &&that) noexcept(\n lib::all::value...>::value)\n : move_constructor(valueless_t{}) {\n this->generic_construct(*this, lib::move(that));\n });\n\n MPARK_VARIANT_MOVE_CONSTRUCTOR(\n Trait::Unavailable,\n move_constructor(move_constructor &&) = delete;);\n\n#undef MPARK_VARIANT_MOVE_CONSTRUCTOR\n\n template \n class copy_constructor;\n\n#define MPARK_VARIANT_COPY_CONSTRUCTOR(copy_constructible_trait, definition) \\\n template \\\n class copy_constructor, copy_constructible_trait> \\\n : public move_constructor> { \\\n using super = move_constructor>; \\\n \\\n public: \\\n MPARK_INHERITING_CTOR(copy_constructor, super) \\\n using super::operator=; \\\n \\\n definition \\\n copy_constructor(copy_constructor &&) = default; \\\n ~copy_constructor() = default; \\\n copy_constructor &operator=(const copy_constructor &) = default; \\\n copy_constructor &operator=(copy_constructor &&) = default; \\\n }\n\n MPARK_VARIANT_COPY_CONSTRUCTOR(\n Trait::TriviallyAvailable,\n copy_constructor(const copy_constructor &that) = default;);\n\n MPARK_VARIANT_COPY_CONSTRUCTOR(\n Trait::Available,\n copy_constructor(const copy_constructor &that)\n : copy_constructor(valueless_t{}) {\n this->generic_construct(*this, that);\n });\n\n MPARK_VARIANT_COPY_CONSTRUCTOR(\n Trait::Unavailable,\n copy_constructor(const copy_constructor &) = delete;);\n\n#undef MPARK_VARIANT_COPY_CONSTRUCTOR\n\n template \n class assignment : public copy_constructor {\n using super = copy_constructor;\n\n public:\n MPARK_INHERITING_CTOR(assignment, super)\n using super::operator=;\n\n template \n inline /* auto & */ auto emplace(Args &&... args)\n -> decltype(this->construct_alt(access::base::get_alt(*this),\n lib::forward(args)...)) {\n this->destroy();\n auto &result = this->construct_alt(access::base::get_alt(*this),\n lib::forward(args)...);\n this->index_ = I;\n return result;\n }\n\n protected:\n#ifndef MPARK_GENERIC_LAMBDAS\n template \n struct assigner {\n template \n inline void operator()(ThisAlt &this_alt, ThatAlt &&that_alt) const {\n self->assign_alt(this_alt, lib::forward(that_alt).value);\n }\n assignment *self;\n };\n#endif\n\n template \n inline void assign_alt(alt &a, Arg &&arg) {\n if (this->index() == I) {\n#ifdef _MSC_VER\n#pragma warning(push)\n#pragma warning(disable : 4244)\n#endif\n a.value = lib::forward(arg);\n#ifdef _MSC_VER\n#pragma warning(pop)\n#endif\n } else {\n struct {\n void operator()(std::true_type) const {\n this_->emplace(lib::forward(arg_));\n }\n void operator()(std::false_type) const {\n this_->emplace(T(lib::forward(arg_)));\n }\n assignment *this_;\n Arg &&arg_;\n } impl{this, lib::forward(arg)};\n impl(lib::bool_constant<\n std::is_nothrow_constructible::value ||\n !std::is_nothrow_move_constructible::value>{});\n }\n }\n\n template \n inline void generic_assign(That &&that) {\n if (this->valueless_by_exception() && that.valueless_by_exception()) {\n // do nothing.\n } else if (that.valueless_by_exception()) {\n this->destroy();\n } else {\n visitation::alt::visit_alt_at(\n that.index(),\n#ifdef MPARK_GENERIC_LAMBDAS\n [this](auto &this_alt, auto &&that_alt) {\n this->assign_alt(\n this_alt, lib::forward(that_alt).value);\n }\n#else\n assigner{this}\n#endif\n ,\n *this,\n lib::forward(that));\n }\n }\n };\n\n template \n class move_assignment;\n\n#define MPARK_VARIANT_MOVE_ASSIGNMENT(move_assignable_trait, definition) \\\n template \\\n class move_assignment, move_assignable_trait> \\\n : public assignment> { \\\n using super = assignment>; \\\n \\\n public: \\\n MPARK_INHERITING_CTOR(move_assignment, super) \\\n using super::operator=; \\\n \\\n move_assignment(const move_assignment &) = default; \\\n move_assignment(move_assignment &&) = default; \\\n ~move_assignment() = default; \\\n move_assignment &operator=(const move_assignment &) = default; \\\n definition \\\n }\n\n MPARK_VARIANT_MOVE_ASSIGNMENT(\n Trait::TriviallyAvailable,\n move_assignment &operator=(move_assignment &&that) = default;);\n\n MPARK_VARIANT_MOVE_ASSIGNMENT(\n Trait::Available,\n move_assignment &\n operator=(move_assignment &&that) noexcept(\n lib::all<(std::is_nothrow_move_constructible::value &&\n std::is_nothrow_move_assignable::value)...>::value) {\n this->generic_assign(lib::move(that));\n return *this;\n });\n\n MPARK_VARIANT_MOVE_ASSIGNMENT(\n Trait::Unavailable,\n move_assignment &operator=(move_assignment &&) = delete;);\n\n#undef MPARK_VARIANT_MOVE_ASSIGNMENT\n\n template \n class copy_assignment;\n\n#define MPARK_VARIANT_COPY_ASSIGNMENT(copy_assignable_trait, definition) \\\n template \\\n class copy_assignment, copy_assignable_trait> \\\n : public move_assignment> { \\\n using super = move_assignment>; \\\n \\\n public: \\\n MPARK_INHERITING_CTOR(copy_assignment, super) \\\n using super::operator=; \\\n \\\n copy_assignment(const copy_assignment &) = default; \\\n copy_assignment(copy_assignment &&) = default; \\\n ~copy_assignment() = default; \\\n definition \\\n copy_assignment &operator=(copy_assignment &&) = default; \\\n }\n\n MPARK_VARIANT_COPY_ASSIGNMENT(\n Trait::TriviallyAvailable,\n copy_assignment &operator=(const copy_assignment &that) = default;);\n\n MPARK_VARIANT_COPY_ASSIGNMENT(\n Trait::Available,\n copy_assignment &operator=(const copy_assignment &that) {\n this->generic_assign(that);\n return *this;\n });\n\n MPARK_VARIANT_COPY_ASSIGNMENT(\n Trait::Unavailable,\n copy_assignment &operator=(const copy_assignment &) = delete;);\n\n#undef MPARK_VARIANT_COPY_ASSIGNMENT\n\n template \n class impl : public copy_assignment> {\n using super = copy_assignment>;\n\n public:\n MPARK_INHERITING_CTOR(impl, super)\n using super::operator=;\n\n impl(const impl&) = default;\n impl(impl&&) = default;\n ~impl() = default;\n impl &operator=(const impl &) = default;\n impl &operator=(impl &&) = default;\n\n template \n inline void assign(Arg &&arg) {\n this->assign_alt(access::base::get_alt(*this),\n lib::forward(arg));\n }\n\n inline void swap(impl &that) {\n if (this->valueless_by_exception() && that.valueless_by_exception()) {\n // do nothing.\n } else if (this->index() == that.index()) {\n visitation::alt::visit_alt_at(this->index(),\n#ifdef MPARK_GENERIC_LAMBDAS\n [](auto &this_alt, auto &that_alt) {\n using std::swap;\n swap(this_alt.value,\n that_alt.value);\n }\n#else\n swapper{}\n#endif\n ,\n *this,\n that);\n } else {\n impl *lhs = this;\n impl *rhs = lib::addressof(that);\n if (lhs->move_nothrow() && !rhs->move_nothrow()) {\n std::swap(lhs, rhs);\n }\n impl tmp(lib::move(*rhs));\n#ifdef MPARK_EXCEPTIONS\n // EXTENSION: When the move construction of `lhs` into `rhs` throws\n // and `tmp` is nothrow move constructible then we move `tmp` back\n // into `rhs` and provide the strong exception safety guarantee.\n try {\n this->generic_construct(*rhs, lib::move(*lhs));\n } catch (...) {\n if (tmp.move_nothrow()) {\n this->generic_construct(*rhs, lib::move(tmp));\n }\n throw;\n }\n#else\n this->generic_construct(*rhs, lib::move(*lhs));\n#endif\n this->generic_construct(*lhs, lib::move(tmp));\n }\n }\n\n private:\n#ifndef MPARK_GENERIC_LAMBDAS\n struct swapper {\n template \n inline void operator()(ThisAlt &this_alt, ThatAlt &that_alt) const {\n using std::swap;\n swap(this_alt.value, that_alt.value);\n }\n };\n#endif\n\n inline constexpr bool move_nothrow() const {\n return this->valueless_by_exception() ||\n lib::array{\n {std::is_nothrow_move_constructible::value...}\n }[this->index()];\n }\n };\n\n#undef MPARK_INHERITING_CTOR\n\n template \n struct is_non_narrowing_convertible {\n template \n static std::true_type test(T(&&)[1]);\n\n template \n static auto impl(int) -> decltype(test({std::declval()}));\n\n template \n static auto impl(...) -> std::false_type;\n\n static constexpr bool value = decltype(impl(0))::value;\n };\n\n template ::value,\n typename = void>\n struct overload_leaf {};\n\n template \n struct overload_leaf {\n using impl = lib::size_constant (*)(T);\n operator impl() const { return nullptr; };\n };\n\n template \n struct overload_leaf<\n Arg,\n I,\n T,\n true\n#if defined(__clang__) || !defined(__GNUC__) || __GNUC__ >= 5\n ,\n lib::enable_if_t<\n std::is_same, bool>::value\n ? std::is_same, bool>::value\n : is_non_narrowing_convertible::value>\n#endif\n > {\n using impl = lib::size_constant (*)(T);\n operator impl() const { return nullptr; };\n };\n\n template \n struct overload_impl {\n private:\n template \n struct impl;\n\n template \n struct impl> : overload_leaf... {};\n\n public:\n using type = impl>;\n };\n\n template \n using overload = typename overload_impl::type;\n\n template \n using best_match = lib::invoke_result_t, Arg>;\n\n template \n struct is_in_place_index : std::false_type {};\n\n template \n struct is_in_place_index> : std::true_type {};\n\n template \n struct is_in_place_type : std::false_type {};\n\n template \n struct is_in_place_type> : std::true_type {};\n\n } // detail\n\n template \n class variant {\n static_assert(0 < sizeof...(Ts),\n \"variant must consist of at least one alternative.\");\n\n static_assert(lib::all::value...>::value,\n \"variant can not have an array type as an alternative.\");\n\n static_assert(lib::all::value...>::value,\n \"variant can not have a reference type as an alternative.\");\n\n static_assert(lib::all::value...>::value,\n \"variant can not have a void type as an alternative.\");\n\n public:\n template <\n typename Front = lib::type_pack_element_t<0, Ts...>,\n lib::enable_if_t::value, int> = 0>\n inline constexpr variant() noexcept(\n std::is_nothrow_default_constructible::value)\n : impl_(in_place_index_t<0>{}) {}\n\n variant(const variant &) = default;\n variant(variant &&) = default;\n\n template <\n typename Arg,\n typename Decayed = lib::decay_t,\n lib::enable_if_t::value, int> = 0,\n lib::enable_if_t::value, int> = 0,\n lib::enable_if_t::value, int> = 0,\n std::size_t I = detail::best_match::value,\n typename T = lib::type_pack_element_t,\n lib::enable_if_t::value, int> = 0>\n inline constexpr variant(Arg &&arg) noexcept(\n std::is_nothrow_constructible::value)\n : impl_(in_place_index_t{}, lib::forward(arg)) {}\n\n template <\n std::size_t I,\n typename... Args,\n typename T = lib::type_pack_element_t,\n lib::enable_if_t::value, int> = 0>\n inline explicit constexpr variant(\n in_place_index_t,\n Args &&... args) noexcept(std::is_nothrow_constructible::value)\n : impl_(in_place_index_t{}, lib::forward(args)...) {}\n\n template <\n std::size_t I,\n typename Up,\n typename... Args,\n typename T = lib::type_pack_element_t,\n lib::enable_if_t &,\n Args...>::value,\n int> = 0>\n inline explicit constexpr variant(\n in_place_index_t,\n std::initializer_list il,\n Args &&... args) noexcept(std::\n is_nothrow_constructible<\n T,\n std::initializer_list &,\n Args...>::value)\n : impl_(in_place_index_t{}, il, lib::forward(args)...) {}\n\n template <\n typename T,\n typename... Args,\n std::size_t I = detail::find_index_sfinae::value,\n lib::enable_if_t::value, int> = 0>\n inline explicit constexpr variant(\n in_place_type_t,\n Args &&... args) noexcept(std::is_nothrow_constructible::value)\n : impl_(in_place_index_t{}, lib::forward(args)...) {}\n\n template <\n typename T,\n typename Up,\n typename... Args,\n std::size_t I = detail::find_index_sfinae::value,\n lib::enable_if_t &,\n Args...>::value,\n int> = 0>\n inline explicit constexpr variant(\n in_place_type_t,\n std::initializer_list il,\n Args &&... args) noexcept(std::\n is_nothrow_constructible<\n T,\n std::initializer_list &,\n Args...>::value)\n : impl_(in_place_index_t{}, il, lib::forward(args)...) {}\n\n ~variant() = default;\n\n variant &operator=(const variant &) = default;\n variant &operator=(variant &&) = default;\n\n template , variant>::value,\n int> = 0,\n std::size_t I = detail::best_match::value,\n typename T = lib::type_pack_element_t,\n lib::enable_if_t<(std::is_assignable::value &&\n std::is_constructible::value),\n int> = 0>\n inline variant &operator=(Arg &&arg) noexcept(\n (std::is_nothrow_assignable::value &&\n std::is_nothrow_constructible::value)) {\n impl_.template assign(lib::forward(arg));\n return *this;\n }\n\n template <\n std::size_t I,\n typename... Args,\n typename T = lib::type_pack_element_t,\n lib::enable_if_t::value, int> = 0>\n inline T &emplace(Args &&... args) {\n return impl_.template emplace(lib::forward(args)...);\n }\n\n template <\n std::size_t I,\n typename Up,\n typename... Args,\n typename T = lib::type_pack_element_t,\n lib::enable_if_t &,\n Args...>::value,\n int> = 0>\n inline T &emplace(std::initializer_list il, Args &&... args) {\n return impl_.template emplace(il, lib::forward(args)...);\n }\n\n template <\n typename T,\n typename... Args,\n std::size_t I = detail::find_index_sfinae::value,\n lib::enable_if_t::value, int> = 0>\n inline T &emplace(Args &&... args) {\n return impl_.template emplace(lib::forward(args)...);\n }\n\n template <\n typename T,\n typename Up,\n typename... Args,\n std::size_t I = detail::find_index_sfinae::value,\n lib::enable_if_t &,\n Args...>::value,\n int> = 0>\n inline T &emplace(std::initializer_list il, Args &&... args) {\n return impl_.template emplace(il, lib::forward(args)...);\n }\n\n inline constexpr bool valueless_by_exception() const noexcept {\n return impl_.valueless_by_exception();\n }\n\n inline constexpr std::size_t index() const noexcept {\n return impl_.index();\n }\n\n template ,\n Dummy>::value &&\n lib::dependent_type,\n Dummy>::value)...>::value,\n int> = 0>\n inline void swap(variant &that) noexcept(\n lib::all<(std::is_nothrow_move_constructible::value &&\n lib::is_nothrow_swappable::value)...>::value) {\n impl_.swap(that.impl_);\n }\n\n private:\n detail::impl impl_;\n\n friend struct detail::access::variant;\n friend struct detail::visitation::variant;\n };\n\n template \n inline constexpr bool holds_alternative(const variant &v) noexcept {\n return v.index() == I;\n }\n\n template \n inline constexpr bool holds_alternative(const variant &v) noexcept {\n return holds_alternative::value>(v);\n }\n\n namespace detail {\n template \n struct generic_get_impl {\n constexpr generic_get_impl(int) noexcept {}\n\n constexpr AUTO_REFREF operator()(V &&v) const\n AUTO_REFREF_RETURN(\n access::variant::get_alt(lib::forward(v)).value)\n };\n\n template \n inline constexpr AUTO_REFREF generic_get(V &&v)\n AUTO_REFREF_RETURN(generic_get_impl(\n holds_alternative(v) ? 0 : (throw_bad_variant_access(), 0))(\n lib::forward(v)))\n } // namespace detail\n\n template \n inline constexpr variant_alternative_t> &get(\n variant &v) {\n return detail::generic_get(v);\n }\n\n template \n inline constexpr variant_alternative_t> &&get(\n variant &&v) {\n return detail::generic_get(lib::move(v));\n }\n\n template \n inline constexpr const variant_alternative_t> &get(\n const variant &v) {\n return detail::generic_get(v);\n }\n\n template \n inline constexpr const variant_alternative_t> &&get(\n const variant &&v) {\n return detail::generic_get(lib::move(v));\n }\n\n template \n inline constexpr T &get(variant &v) {\n return get::value>(v);\n }\n\n template \n inline constexpr T &&get(variant &&v) {\n return get::value>(lib::move(v));\n }\n\n template \n inline constexpr const T &get(const variant &v) {\n return get::value>(v);\n }\n\n template \n inline constexpr const T &&get(const variant &&v) {\n return get::value>(lib::move(v));\n }\n\n namespace detail {\n\n template \n inline constexpr /* auto * */ AUTO generic_get_if(V *v) noexcept\n AUTO_RETURN(v && holds_alternative(*v)\n ? lib::addressof(access::variant::get_alt(*v).value)\n : nullptr)\n\n } // namespace detail\n\n template \n inline constexpr lib::add_pointer_t>>\n get_if(variant *v) noexcept {\n return detail::generic_get_if(v);\n }\n\n template \n inline constexpr lib::add_pointer_t<\n const variant_alternative_t>>\n get_if(const variant *v) noexcept {\n return detail::generic_get_if(v);\n }\n\n template \n inline constexpr lib::add_pointer_t\n get_if(variant *v) noexcept {\n return get_if::value>(v);\n }\n\n template \n inline constexpr lib::add_pointer_t\n get_if(const variant *v) noexcept {\n return get_if::value>(v);\n }\n\n namespace detail {\n template \n struct convert_to_bool {\n template \n inline constexpr bool operator()(Lhs &&lhs, Rhs &&rhs) const {\n static_assert(std::is_convertible,\n bool>::value,\n \"relational operators must return a type\"\n \" implicitly convertible to bool\");\n return lib::invoke(\n RelOp{}, lib::forward(lhs), lib::forward(rhs));\n }\n };\n } // namespace detail\n\n template \n inline constexpr bool operator==(const variant &lhs,\n const variant &rhs) {\n using detail::visitation::variant;\n using equal_to = detail::convert_to_bool;\n#ifdef MPARK_CPP14_CONSTEXPR\n if (lhs.index() != rhs.index()) return false;\n if (lhs.valueless_by_exception()) return true;\n return variant::visit_value_at(lhs.index(), equal_to{}, lhs, rhs);\n#else\n return lhs.index() == rhs.index() &&\n (lhs.valueless_by_exception() ||\n variant::visit_value_at(lhs.index(), equal_to{}, lhs, rhs));\n#endif\n }\n\n template \n inline constexpr bool operator!=(const variant &lhs,\n const variant &rhs) {\n using detail::visitation::variant;\n using not_equal_to = detail::convert_to_bool;\n#ifdef MPARK_CPP14_CONSTEXPR\n if (lhs.index() != rhs.index()) return true;\n if (lhs.valueless_by_exception()) return false;\n return variant::visit_value_at(lhs.index(), not_equal_to{}, lhs, rhs);\n#else\n return lhs.index() != rhs.index() ||\n (!lhs.valueless_by_exception() &&\n variant::visit_value_at(lhs.index(), not_equal_to{}, lhs, rhs));\n#endif\n }\n\n template \n inline constexpr bool operator<(const variant &lhs,\n const variant &rhs) {\n using detail::visitation::variant;\n using less = detail::convert_to_bool;\n#ifdef MPARK_CPP14_CONSTEXPR\n if (rhs.valueless_by_exception()) return false;\n if (lhs.valueless_by_exception()) return true;\n if (lhs.index() < rhs.index()) return true;\n if (lhs.index() > rhs.index()) return false;\n return variant::visit_value_at(lhs.index(), less{}, lhs, rhs);\n#else\n return !rhs.valueless_by_exception() &&\n (lhs.valueless_by_exception() || lhs.index() < rhs.index() ||\n (lhs.index() == rhs.index() &&\n variant::visit_value_at(lhs.index(), less{}, lhs, rhs)));\n#endif\n }\n\n template \n inline constexpr bool operator>(const variant &lhs,\n const variant &rhs) {\n using detail::visitation::variant;\n using greater = detail::convert_to_bool;\n#ifdef MPARK_CPP14_CONSTEXPR\n if (lhs.valueless_by_exception()) return false;\n if (rhs.valueless_by_exception()) return true;\n if (lhs.index() > rhs.index()) return true;\n if (lhs.index() < rhs.index()) return false;\n return variant::visit_value_at(lhs.index(), greater{}, lhs, rhs);\n#else\n return !lhs.valueless_by_exception() &&\n (rhs.valueless_by_exception() || lhs.index() > rhs.index() ||\n (lhs.index() == rhs.index() &&\n variant::visit_value_at(lhs.index(), greater{}, lhs, rhs)));\n#endif\n }\n\n template \n inline constexpr bool operator<=(const variant &lhs,\n const variant &rhs) {\n using detail::visitation::variant;\n using less_equal = detail::convert_to_bool;\n#ifdef MPARK_CPP14_CONSTEXPR\n if (lhs.valueless_by_exception()) return true;\n if (rhs.valueless_by_exception()) return false;\n if (lhs.index() < rhs.index()) return true;\n if (lhs.index() > rhs.index()) return false;\n return variant::visit_value_at(lhs.index(), less_equal{}, lhs, rhs);\n#else\n return lhs.valueless_by_exception() ||\n (!rhs.valueless_by_exception() &&\n (lhs.index() < rhs.index() ||\n (lhs.index() == rhs.index() &&\n variant::visit_value_at(lhs.index(), less_equal{}, lhs, rhs))));\n#endif\n }\n\n template \n inline constexpr bool operator>=(const variant &lhs,\n const variant &rhs) {\n using detail::visitation::variant;\n using greater_equal = detail::convert_to_bool;\n#ifdef MPARK_CPP14_CONSTEXPR\n if (rhs.valueless_by_exception()) return true;\n if (lhs.valueless_by_exception()) return false;\n if (lhs.index() > rhs.index()) return true;\n if (lhs.index() < rhs.index()) return false;\n return variant::visit_value_at(lhs.index(), greater_equal{}, lhs, rhs);\n#else\n return rhs.valueless_by_exception() ||\n (!lhs.valueless_by_exception() &&\n (lhs.index() > rhs.index() ||\n (lhs.index() == rhs.index() &&\n variant::visit_value_at(\n lhs.index(), greater_equal{}, lhs, rhs))));\n#endif\n }\n\n struct monostate {};\n\n inline constexpr bool operator<(monostate, monostate) noexcept {\n return false;\n }\n\n inline constexpr bool operator>(monostate, monostate) noexcept {\n return false;\n }\n\n inline constexpr bool operator<=(monostate, monostate) noexcept {\n return true;\n }\n\n inline constexpr bool operator>=(monostate, monostate) noexcept {\n return true;\n }\n\n inline constexpr bool operator==(monostate, monostate) noexcept {\n return true;\n }\n\n inline constexpr bool operator!=(monostate, monostate) noexcept {\n return false;\n }\n\n#ifdef MPARK_CPP14_CONSTEXPR\n namespace detail {\n\n inline constexpr bool any(std::initializer_list bs) {\n for (bool b : bs) {\n if (b) {\n return true;\n }\n }\n return false;\n }\n\n } // namespace detail\n\n template \n inline constexpr decltype(auto) visit(Visitor &&visitor, Vs &&... vs) {\n return (!detail::any({vs.valueless_by_exception()...})\n ? (void)0\n : throw_bad_variant_access()),\n detail::visitation::variant::visit_value(\n lib::forward(visitor), lib::forward(vs)...);\n }\n#else\n namespace detail {\n\n template \n inline constexpr bool all_impl(const lib::array &bs,\n std::size_t idx) {\n return idx >= N || (bs[idx] && all_impl(bs, idx + 1));\n }\n\n template \n inline constexpr bool all(const lib::array &bs) {\n return all_impl(bs, 0);\n }\n\n } // namespace detail\n\n template \n inline constexpr DECLTYPE_AUTO visit(Visitor &&visitor, Vs &&... vs)\n DECLTYPE_AUTO_RETURN(\n (detail::all(\n lib::array{{!vs.valueless_by_exception()...}})\n ? (void)0\n : throw_bad_variant_access()),\n detail::visitation::variant::visit_value(lib::forward(visitor),\n lib::forward(vs)...))\n#endif\n\n template \n inline auto swap(variant &lhs,\n variant &rhs) noexcept(noexcept(lhs.swap(rhs)))\n -> decltype(lhs.swap(rhs)) {\n lhs.swap(rhs);\n }\n\n namespace detail {\n\n template \n using enabled_type = T;\n\n namespace hash {\n\n template \n constexpr bool meets_requirements() noexcept {\n return std::is_copy_constructible::value &&\n std::is_move_constructible::value &&\n lib::is_invocable_r::value;\n }\n\n template \n constexpr bool is_enabled() noexcept {\n using H = std::hash;\n return meets_requirements() &&\n std::is_default_constructible::value &&\n std::is_copy_assignable::value &&\n std::is_move_assignable::value;\n }\n\n } // namespace hash\n\n } // namespace detail\n\n#undef AUTO\n#undef AUTO_RETURN\n\n#undef AUTO_REFREF\n#undef AUTO_REFREF_RETURN\n\n#undef DECLTYPE_AUTO\n#undef DECLTYPE_AUTO_RETURN\n\n} // namespace mpark\n\nnamespace std {\n\n template \n struct hash,\n mpark::lib::enable_if_t>()...>::value>>> {\n using argument_type = mpark::variant;\n using result_type = std::size_t;\n\n inline result_type operator()(const argument_type &v) const {\n using mpark::detail::visitation::variant;\n std::size_t result =\n v.valueless_by_exception()\n ? 299792458 // Random value chosen by the universe upon creation\n : variant::visit_alt(\n#ifdef MPARK_GENERIC_LAMBDAS\n [](const auto &alt) {\n using alt_type = mpark::lib::decay_t;\n using value_type = mpark::lib::remove_const_t<\n typename alt_type::value_type>;\n return hash{}(alt.value);\n }\n#else\n hasher{}\n#endif\n ,\n v);\n return hash_combine(result, hash{}(v.index()));\n }\n\n private:\n#ifndef MPARK_GENERIC_LAMBDAS\n struct hasher {\n template \n inline std::size_t operator()(const Alt &alt) const {\n using alt_type = mpark::lib::decay_t;\n using value_type =\n mpark::lib::remove_const_t;\n return hash{}(alt.value);\n }\n };\n#endif\n\n static std::size_t hash_combine(std::size_t lhs, std::size_t rhs) {\n return lhs ^= rhs + 0x9e3779b9 + (lhs << 6) + (lhs >> 2);\n }\n };\n\n template <>\n struct hash {\n using argument_type = mpark::monostate;\n using result_type = std::size_t;\n\n inline result_type operator()(const argument_type &) const noexcept {\n return 66740831; // return a fundamentally attractive random value.\n }\n };\n\n} // namespace std\n\n#endif // MPARK_VARIANT_HPP\n" }, { "path": "LICENSE", "content": "MIT License\n\nCopyright (c) 2020 Xinlei Wang, Yuxing Qiu, Stuart R. Slattery, Yu Fang, Minchen Li, Song-Chun Zhu, Yixin Zhu, Min Tang, Dinesh Manocha, Chenfanfu Jiang\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n" }, { "path": "Library/CMakeLists.txt", "content": "add_subdirectory(MnSystem)" }, { "path": "Library/MnBase/Algorithm/MappingKernels.cuh", "content": "#ifndef MAPPING_KERNELS_CUH\n#define MAPPING_KERNELS_CUH\n#include \n\n#define PRINT_FIRST_INDICES 0\n\nnamespace mn {\n\ntemplate\n__global__ void mark_boundary(int num, const EntryType* entries, MarkerType* marks, BinaryOp op) {\n\tuint32_t idx = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(idx >= num) {\n\t\treturn;\n\t}\n\t/// mark the tails of all segments\n\tmarks[idx] = (idx != num - 1) ? op(entries[idx], entries[idx + 1]) : 1;\n}\n\ntemplate\n__global__ void set_inverse(int num, const IndexType* map, IndexType* map_inv) {\n\tuint32_t idx = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(idx >= num) {\n\t\treturn;\n\t}\n\tauto map_idx = map[idx];\n\tif(idx == 0 || map_idx != map[idx - 1]) {\n\t\tmap_inv[map_idx] = idx;\n#if PRINT_FIRST_INDICES\n\t\tif(map_idx < 5) {\n\t\t\tprintf(\"%d-th block starts at %d\\n\", map_idx, map_inv[map_idx]);\n\t\t}\n#endif\n\t}\n\tif(idx == num - 1) {\n\t\tmap_inv[map_idx + 1] = num;\n\t}\n#if PRINT_FIRST_INDICES\n\tif(idx < 5) {\n\t\tprintf(\"%d-th particle belongs to block %d\\n\", idx, map_idx);\n\t}\n#endif\n}\n\ntemplate\n__global__ void exclusive_scan_inverse(CounterType num, const IndexType* map, IndexType* map_inv) {\n\tconst uint32_t idx = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(idx >= num) {\n\t\treturn;\n\t}\n\n\tconst auto map_idx = map[idx];\n\tif(map_idx != map[idx + 1]) {\n\t\tmap_inv[map_idx] = idx;\n\t}\n}\n\ntemplate\n__global__ void map_inverse(int num, const IndexType* map, IndexType* map_inv) {\n\tuint32_t idx = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(idx >= num) {\n\t\treturn;\n\t}\n\tmap_inv[map[idx]] = idx;\n}\n\ntemplate\n__global__ void set_range_inverse(int count, const MappingType* to_packed_range_map, const MappingType* to_range_map, CounterType* num_packed_range, MappingType* range_ids, MappingType* range_left_bound, MappingType* range_right_bound) {\n\tuint32_t idx = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(idx >= count) {\n\t\treturn;\n\t}\n\tauto packed_range_idx = to_packed_range_map[idx];\n\tauto range_idx\t\t = to_range_map[idx];\n\tbool l_tag\t\t\t = idx == 0 || range_idx != to_range_map[idx - 1];\n\tbool r_tag\t\t\t = idx == count - 1 || range_idx != to_range_map[idx + 1];\n\t/// left bound\n\tif(l_tag) {\n\t\trange_left_bound[packed_range_idx] = idx;\n\t\trange_ids[packed_range_idx]\t\t = range_idx;\n#if PRINT_FIRST_INDICES\n\t\tif(packed_range_idx == 0) {\n\t\t\tprintf(\"%d-th block st (%d): %d\\n\", packed_range_idx, range_idx, range_left_bound[packed_range_idx]);\n\t\t}\n#endif\n\t}\n\t/// right bound\n\tif(r_tag) {\n\t\trange_right_bound[packed_range_idx] = idx + 1;\n#if PRINT_FIRST_INDICES\n\t\tif(packed_range_idx == 0) {\n\t\t\tprintf(\"%d-th block ed: %d\\n\", packed_range_idx, range_right_bound[packed_range_idx]);\n\t\t}\n#endif\n\t}\n\tif(idx == count - 1) {\n\t\t*num_packed_range = packed_range_idx + 1;\n\t}\n}\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Algorithm/ParallelPatterns.cuh", "content": "#ifndef PARALLEL_PATTERNS_CUH\n#define PARALLEL_PATTERNS_CUH\n#include \"MnSystem/Cuda/HostUtils.hpp\"\n#include \"MnSystem/Cuda/MemoryUtils.cuh\"\n//#include \n//#include \n//#include \n#include \n#include \n\n//#include \n\n#define ENABLE_KEY_FUNCTIONS 0\n\nnamespace mn {\n\n/// sequence\ntemplate\nvoid sequence(std::size_t count, T* array, T value = 0, cudaStream_t stream = cudaStreamDefault) {\n\tcheckThrustErrors(thrust::sequence(thrust::cuda::par.on(stream), getDevicePtr(array), getDevicePtr(array) + count, value));\n}\n\n/// reduece\ntemplate\nT reduce(std::size_t count, T* array, T value = 0, cudaStream_t stream = cudaStreamDefault) {\n\tT result = (thrust::reduce(thrust::cuda::par.on(stream), getDevicePtr(array), getDevicePtr(array) + count, value));\n\treturn result;\n}\n\n/// fill\ntemplate\nvoid fill_with(std::size_t count, T* array, T value, cudaStream_t stream = cudaStreamDefault) {\n\tcheckThrustErrors(thrust::fill(thrust::cuda::par.on(stream), getDevicePtr(array), getDevicePtr(array) + count, value));\n}\ntemplate\nvoid fill_with(std::size_t count, AttribPort attribs, T value, cudaStream_t stream = cudaStreamDefault) {\n\tfor(int i = 0; i < (int) Size; ++i) {\n\t\tfill_with(count, attribs[i], value, stream);\n\t}\n}\n/// set\ntemplate\n__global__ void set_values(std::size_t num, T* array, ValueOp op) {\n\tuint32_t idx = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(idx >= num) {\n\t\treturn;\n\t}\n\tarray[idx] = op(idx);\n}\ntemplate\nvoid set_with(std::size_t count, T* array, ValueOp value_op) {\n\tcuda_launch({(count + 255) / 256, 256}, set_values, count, array, value_op);\n}\ntemplate\nvoid set_with(std::size_t count, AttribPort attribs, ValueOp value_op) {\n\tfor(int i = 0; i < Size; ++i) {\n\t\tset_with(count, attribs[i], value_op);\n\t}\n}\n\n#if ENABLE_KEY_FUNCTIONS\ntemplate\nvoid sort_by_key(std::size_t count, const Key* keys_in, const Value* values_in, Key* keys_out, Value* values_out, cudaStream_t stream = cudaStreamDefault) {\n\tvoid* d_temp_storage\t\t = nullptr;\n\tstd::size_t temp_storage_bytes = 0;\n\tcheckCudaErrors(cub::DeviceRadixSort::SortPairs(d_temp_storage, temp_storage_bytes, keys_in, keys_out, values_in, values_out, count, 0, sizeof(Key) * 8, stream));\n\td_temp_storage = cudaMemBorrow(temp_storage_bytes);///< more managable memory consumption\n\t//printf(\"requires %lu bytes for sort_by_key\\n\", temp_storage_bytes);\n\tcheckCudaErrors(cub::DeviceRadixSort::SortPairs(d_temp_storage, temp_storage_bytes, keys_in, keys_out, values_in, values_out, count, 0, sizeof(Key) * 8, stream));\n}\n\ntemplate\nvoid sort_by_key_bits(std::size_t count, const Key* keys_in, const Value* values_in, Key* keys_out, Value* values_out, int least_sig_bits = 12, int most_sig_bits = sizeof(Key) * 8, cudaStream_t stream = cudaStreamDefault) {\n\tvoid* d_temp_storage\t\t = nullptr;\n\tstd::size_t temp_storage_bytes = 0;\n\tcheckCudaErrors(cub::DeviceRadixSort::SortPairs(d_temp_storage, temp_storage_bytes, keys_in, keys_out, values_in, values_out, count, least_sig_bits, most_sig_bits, stream));\n\td_temp_storage = cudaMemBorrow(temp_storage_bytes);///< more managable memory consumption\n\t//printf(\"requires %lu bytes for sort_by_key\\n\", temp_storage_bytes);\n\tcheckCudaErrors(cub::DeviceRadixSort::SortPairs(d_temp_storage, temp_storage_bytes, keys_in, keys_out, values_in, values_out, count, least_sig_bits, most_sig_bits, stream));\n}\n\n/// exclusive scan\ntemplate\nvoid exclusive_scan(std::size_t count, const TIn* input, TOut* output, BinaryOp&& op, cudaStream_t stream = cudaStreamDefault) {\n\tvoid* d_temp_storage\t\t = nullptr;\n\tstd::size_t temp_storage_bytes = 0;\n\tcheckCudaErrors(cub::DeviceScan::ExclusiveScan(d_temp_storage, temp_storage_bytes, input, output, std::forward(op), 0, count, stream));\n\td_temp_storage = cudaMemBorrow(temp_storage_bytes);///< more managable memory consumption\n\t//printf(\"requires %llu bytes for exclusive scan\\n\", (long long unsigned int)temp_storage_bytes);\n\tcheckCudaErrors(cub::DeviceScan::ExclusiveScan(d_temp_storage, temp_storage_bytes, input, output, std::forward(op), 0, count, stream));\n}\n\n/// count if\ntemplate\nvoid select_if(std::size_t inputcount, const T* input, CounterType* outputcount, T* output, UnaryOp&& op, cudaStream_t stream = cudaStreamDefault) {\n\tvoid* d_temp_storage\t\t = nullptr;\n\tstd::size_t temp_storage_bytes = 0;\n\tcub::DeviceSelect::If(d_temp_storage, temp_storage_bytes, input, output, outputcount, inputcount, std::forward(op), stream);\n\td_temp_storage = cudaMemBorrow(temp_storage_bytes);///< more managable memory consumption\n\t//printf(\"requires %llu bytes for select if\\n\", (long long unsigned int)temp_storage_bytes);\n\tcub::DeviceSelect::If(d_temp_storage, temp_storage_bytes, input, output, outputcount, inputcount, std::forward(op), stream);\n}\n#endif\n\n}// namespace mn\n\n#endif\n" }, { "path": "Library/MnBase/Algorithm/SortKernels.cuh", "content": "#ifndef SORT_KERNELS_CUH\n#define SORT_KERNELS_CUH\n#include \n\nnamespace mn {\n\ntemplate\n__global__ void gather_entry(int num, const AttribPort from, AttribPort to, const IndexType* prev) {\n\tuint32_t idx = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(idx >= num) {\n\t\treturn;\n\t}\n\tfor(int i = 0; i < Size; ++i) {\n\t\tto[i][idx] = from[i][prev[idx]];\n\t}\n}\n\ntemplate\n__global__ void scatter_entry(int num, const AttribPort from, AttribPort to, const IndexType* _next) {\n\tuint32_t idx = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(idx >= num) {\n\t\treturn;\n\t}\n\tfor(int i = 0; i < Size; ++i) {\n\t\tto[i][_next[idx]] = from[i][idx];\n\t}\n}\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Concurrency/Concurrency.h", "content": "#ifndef CONCURRENCY_H\n#define CONCURRENCY_H\n\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n\n#include \"MnBase/Meta/Optional.h\"\n\nnamespace mn {\n\ntemplate\ninline auto really_async(F&& f, Ts&&... params) {\n\treturn std::async(std::launch::async, std::forward(f), std::forward(params)...);\n}\n\n/// <>\ntemplate\nclass ThreadsafeQueue {\n private:\n\tmutable std::mutex mut;\n\tstd::queue data_queue;\n\tstd::condition_variable data_cond;\n\n public:\n\tThreadsafeQueue() = default;\n\t~ThreadsafeQueue() = default;\n\n\tThreadsafeQueue(ThreadsafeQueue const& other) noexcept {\n\t\tstd::lock_guard lk(other.mut);\n\t\tdata_queue = other.data_queue;\n\t}\n\n\tThreadsafeQueue(ThreadsafeQueue&& other) noexcept {\n\t\tstd::lock_guard lk(other.mut);\n\t\tdata_queue = std::move(other.data_queue);\n\t}\n\n\tThreadsafeQueue& operator=(ThreadsafeQueue const& other) noexcept {\n\t\tif(&other != this) {\n\t\t\tstd::lock_guard lk(other.mut);\n\t\t\tdata_queue = other.data_queue;\n\t\t}\n\n\t\treturn *this;\n\t}\n\n\tThreadsafeQueue& operator=(ThreadsafeQueue&& other) noexcept {\n\t\tif(&other != this) {\n\t\t\tstd::lock_guard lk(other.mut);\n\t\t\tdata_queue = std::move(other.data_queue);\n\t\t}\n\n\t\treturn *this;\n\t}\n\n\tvoid push(T new_value) {\n\t\tstd::lock_guard lk(mut);\n\t\tdata_queue.push(new_value);\n\t\tdata_cond.notify_one();\n\t}\n\n\tvoid wait_and_pop(T& value) {\n\t\t/// spinlock should be better\n\t\tstd::unique_lock lk(mut);\n\t\tdata_cond.wait(lk, [this] {\n\t\t\treturn !data_queue.empty();\n\t\t});\n\t\tvalue = data_queue.front();\n\t\tdata_queue.pop();\n\t}\n\n\tdecltype(auto) wait_and_pop() {\n\t\t/// spinlock should be better\n\t\tstd::unique_lock lk(mut);\n\t\tdata_cond.wait(lk, [this] {\n\t\t\treturn !data_queue.empty();\n\t\t});\n\t\tT value = data_queue.front();\n\t\tdata_queue.pop();\n\t\treturn value;\n\t}\n\n\tstd::shared_ptr wait_and_pop_ptr() {\n\t\tstd::unique_lock lk(mut);\n\t\tdata_cond.wait(lk, [this] {\n\t\t\treturn !data_queue.empty();\n\t\t});\n\t\tstd::shared_ptr res(std::make_shared(data_queue.front()));\n\t\tdata_queue.pop();\n\t\treturn res;\n\t}\n\n\tbool try_pop(T& value) {\n\t\tstd::lock_guard lk(mut);\n\t\tif(data_queue.empty()) {\n\t\t\treturn false;\n\t\t}\n\t\tvalue = data_queue.front();\n\t\tdata_queue.pop();\n\t\treturn true;\n\t}\n\n\tdecltype(auto) try_pop() {\n\t\tstd::lock_guard lk(mut);\n\t\tif(data_queue.empty()) {\n\t\t\treturn optional {};\n\t\t}\n\t\toptional value {data_queue.front()};\n\t\tdata_queue.pop();\n\t\treturn value;\n\t}\n\n\tstd::shared_ptr try_pop_ptr() {\n\t\tstd::lock_guard lk(mut);\n\t\tif(data_queue.empty()) {\n\t\t\treturn std::shared_ptr();\n\t\t}\n\t\tstd::shared_ptr res(std::make_shared(data_queue.front()));\n\t\tdata_queue.pop();\n\t\treturn res;\n\t}\n\n\tbool empty() const {\n\t\tstd::lock_guard lk(mut);\n\t\treturn data_queue.empty();\n\t}\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/DataStructure/Bvh/Bvh.cuh", "content": "#ifndef BVH_CUH\n#define BVH_CUH\n#include \n\n#include \n\nnamespace mn {}\n\n#endif" }, { "path": "Library/MnBase/DataStructure/FSM/FiniteStateMachine.h", "content": "#ifndef FINITE_STATE_MACHINE_H\n#define FINITE_STATE_MACHINE_H\n#include \"MnBase/Meta/Optional.h\"\n#include \"MnBase/Meta/Polymorphism.h\"\n#include \"MnBase/Object/Property.h\"\n\nnamespace mn {\n\n/// CRTP\ntemplate\nclass FSM {\n private:\n\tStateVariant state;\n\n public:\n\texplicit FSM(StateVariant&& state)\n\t\t: state(state) {}\n\n\ttemplate\n\tvoid dispatch(Event&& event) {\n\t\tDerived& self = static_cast(*this);\n\t\tauto newState = match(state)([this, &event](auto& s) -> optional {\n\t\t\treturn self.onEvent(s, std::forward(event));\n\t\t});\n\t\t//[&](auto & s) ->optional { return self.onEvent(s, (event)); });\n\t\tif(newState) {\n\t\t\tstate = *std::move(newState);\n\t\t}\n\t}\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/DataStructure/Hash/Hash.cuh", "content": "#ifndef HASH_CUH\n#define HASH_CUH\n#include \"MnBase/AggregatedAttribs.cuh\"\n#include \"MnBase/Math/Bit/Bits.h\"\n#include \"MnSystem/Cuda/HostUtils.hpp\"\n///< For multiGPU_TEST Flag only\n#include \"MnWorld/SimulationSetting.h\"\n\n#define NO_OPT_HASH_TABLE 0\n\nnamespace mn {\n#if NO_OPT_HASH_TABLE\ntemplate>\n#\tif MULTI_GPU_TEST///< HashTable on UM\nstruct HashTable : public CudaAttribs {\n\tusing Base = CudaAttribs;\n#\telse\nstruct HashTable : public CudaAttribs {\n\tusing Base = CudaAttribs;\n#\tendif\n#endif\n\ttemplate>\n\tstruct HashTable : public CudaAttribs {\n\t\tusing Base = CudaAttribs;\n\t\tstruct CudaPort {\n\t\t\tstatic_assert(sizeof(KeyType) == 8 || sizeof(KeyType) == 4, \"Hashtable KeyType neither 64-bit or 32-bit!\\n\");\n\t\t\tstatic_assert(sizeof(unsigned long long int) == 8 && sizeof(unsigned int) == 4, \"\\'unsigned long long int\\' not 64-bit or \\'unsigned int\\' not 32-bit!\\n\");\n\n\t\t\tusing KT = std::conditional_t;\n\t\t\tusing VT = ValueType;\n\n\t\t\tenum : uint64_t {\n\t\t\t\tHASH_KEY_OFFSET = 127\n\t\t\t};\n\t\t\tenum : KT {\n\t\t\t\tSENTINEL_VALUE = (KT) -1\n\t\t\t};\n\n\t\t\tstd::size_t mask;\n\t\t\tKT* key_table;///< should be cuda compatible!\n\t\t\tVT* value_table;\n\t\t\tVT* entry_count;\n\n\t\t\tCudaPort(std::size_t mask, KeyType* key_table, ValueType* val_table, ValueType* entry_count)\n\t\t\t\t: mask {std::move(mask)}\n\t\t\t\t, key_table {static_cast(static_cast(key_table))}\n\t\t\t\t, value_table {static_cast(static_cast(val_table))}\n\t\t\t\t, entry_count {static_cast(static_cast(entry_count))} {}\n\n\t\t\ttemplate\n\t\t\t__forceinline__ __device__ void insert(KeyT&& key) {\n\t\t\t\tKeyType hashkey = std::forward(key) & mask;\n\t\t\t\tKeyType ori;\n\n\t\t\t\twhile((ori = key_table[hashkey]) != std::forward(key)) {\n\t\t\t\t\tif(ori == SENTINEL_VALUE) {\n\t\t\t\t\t\tori = atomicCAS(key_table + hashkey, SENTINEL_VALUE, std::forward(key));\n\t\t\t\t\t}\n\t\t\t\t\tif(key_table[hashkey] == std::forward(key)) {///< found\n\t\t\t\t\t\tif(ori == SENTINEL_VALUE) {\n\t\t\t\t\t\t\tvalue_table[hashkey] = atomicAdd(entry_count, 1);///< created a record\n\t\t\t\t\t\t}\n\t\t\t\t\t\tbreak;\n\t\t\t\t\t}\n\t\t\t\t\thashkey += HASH_KEY_OFFSET;///< search next entry\n\t\t\t\t\tif(hashkey > mask) {\n\t\t\t\t\t\thashkey = hashkey & mask;\n\t\t\t\t\t}\n\t\t\t\t};\n\t\t\t}\n\n\t\t\ttemplate\n\t\t\t__forceinline__ __device__ void insert(KeyT&& key, KeyT* records, RecoverKeyOp recover_op) {\n\t\t\t\tKeyType hashkey = std::forward(key) & mask;\n\t\t\t\tKeyType ori;\n\n\t\t\t\twhile((ori = key_table[hashkey]) != std::forward(key)) {\n\t\t\t\t\tif(ori == SENTINEL_VALUE) {\n\t\t\t\t\t\tori = atomicCAS(key_table + hashkey, SENTINEL_VALUE, std::forward(key));\n\t\t\t\t\t}\n\t\t\t\t\tif(key_table[hashkey] == std::forward(key)) {///< found\n\t\t\t\t\t\tif(ori == SENTINEL_VALUE) {\n\t\t\t\t\t\t\trecords[value_table[hashkey] = atomicAdd(entry_count, 1)] = recover_op(std::forward(key));///< created a record\n\t\t\t\t\t\t}\n\t\t\t\t\t\tbreak;\n\t\t\t\t\t}\n\t\t\t\t\thashkey += HASH_KEY_OFFSET;///< search next entry\n\t\t\t\t\tif(hashkey > mask) {\n\t\t\t\t\t\thashkey = hashkey & mask;\n\t\t\t\t\t}\n\t\t\t\t};\n\t\t\t}\n\n\t\t\ttemplate\n\t\t\t__forceinline__ __device__ auto query(KeyT&& key) const -> ValueType {\n\t\t\t\tKeyType hashkey = std::forward(key) & mask;\n\t\t\t\tKeyType ori;\n\n\t\t\t\twhile((ori = key_table[hashkey]) != std::forward(key)) {\n\t\t\t\t\tif(ori == SENTINEL_VALUE) {\n\t\t\t\t\t\treturn -1;\n\t\t\t\t\t}\n\t\t\t\t\thashkey += HASH_KEY_OFFSET;///< search next entry\n\t\t\t\t\tif(hashkey > mask) {\n\t\t\t\t\t\thashkey = hashkey & mask;\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\treturn value_table[hashkey];\n\t\t\t}\n\t\t};\n\n\t\tstd::size_t entry_size;\n\t\tstd::size_t table_size;\n\t\tstd::size_t mask;\n\t\tKeyType* key_table;\n\t\tValueType* value_table;\n\t\tValueType* entry_count;\n\n\t\tHashTable() = delete;\n\n\t\ttemplate\n\t\tHashTable(Integer size)\n\t\t\t: Base {static_cast(1) << bit_count(estimate_table_size(size))}\n\t\t\t, entry_size {size}\n\t\t\t, table_size {static_cast(1) << bit_count(estimate_table_size(size))} {\n\t\t\tstatic_assert(std::is_integral::value, \"Hashtable value type is not integer.\");\n\t\t\tmask = table_size - 1;\n\t\t\t//printf(\"required size: %llu, actual alloced size: %llu, mask: %llx(%llu)\\n\", size, table_size, mask, mask);\n\t\t\tkey_table\t= static_cast(static_cast(Base::_attribs[0]));\n\t\t\tvalue_table = static_cast(static_cast(Base::_attribs[1]));\n\t\t\t// #if MULTI_GPU_TEST\n\t\t\t// \t\t\tcheckCudaErrors(cudaMallocManaged((void**)&entry_count, sizeof(int)));\n\t\t\t// #else\n\t\t\t// \t\t\tcheckCudaErrors(cudaMalloc((void**)&entry_count, sizeof(int)));\n\t\t\t// #endif\n\t\t\tif(Opt == 1) {\n\t\t\t\tcheckCudaErrors(cudaMallocManaged(static_cast(static_cast(&entry_count)), sizeof(int)));\n\t\t\t} else {\n\t\t\t\tcheckCudaErrors(cudaMalloc(static_cast(static_cast(&entry_count)), sizeof(int)));\n\t\t\t}\n\t\t}\n\n\t\t~HashTable() {\n\t\t\tcudaFree(entry_count);\n\t\t}\n\n\t\tauto estimate_table_size(std::size_t entry_size) const noexcept {\n\t\t\treturn entry_size << 5;\n\t\t}\n\t\t// auto estimate_table_size(std::size_t entry_size) const noexcept { return entry_size << 5; }\n\n\t\tvoid clear_count() {\n\t\t\tcudaMemset(entry_count, 0, sizeof(ValueType));\n\t\t}\n\t\tvoid clear_count(cudaStream_t stream) {\n\t\t\tcudaMemsetAsync(entry_count, 0, sizeof(ValueType), stream);\n\t\t}\n\t\tvoid clear() {\n\t\t\tcudaMemset(entry_count, 0, sizeof(ValueType));\n\t\t\tcudaMemset(key_table, 0xff, sizeof(KeyType) * table_size);\n\t\t\tcudaMemset(value_table, 0xff, sizeof(ValueType) * table_size);\n\t\t}\n\t\tvoid clear(cudaStream_t stream) {\n\t\t\tcudaMemsetAsync(entry_count, 0, sizeof(ValueType), stream);\n\t\t\tcudaMemsetAsync(key_table, 0xff, sizeof(KeyType) * table_size, stream);\n\t\t\tcudaMemsetAsync(value_table, 0xff, sizeof(ValueType) * table_size, stream);\n\t\t}\n\t\tauto get_port() {\n\t\t\treturn CudaPort {mask, key_table, value_table, entry_count};\n\t\t}\n\t\tvoid retrieve_entry_count(ValueType* addr, cudaStream_t stream = cudaStreamDefault) {\n\t\t\tcudaMemcpyAsync(addr, entry_count, sizeof(ValueType), cudaMemcpyDeviceToHost, stream);\n\t\t}\n#if MULTI_GPU_TEST\n\t\tvoid um_advise_access_by_init(int dev_id) {\n#\tif DEBUG\n\t\t\tprintf(\"[DEBUG] Setting HashTable_UM_Advice AccessBy for Dev %d\\n\", dev_id);\n#\tendif\n\t\t\t// checkCudaErrors(cudaMemAdvise(entry_count, sizeof(int), cudaMemAdviseSetAccessedBy, dev_id));\n\t\t\t// checkCudaErrors(cudaMemAdvise(key_table, sizeof(KeyType) * table_size, cudaMemAdviseSetAccessedBy, dev_id));\n\t\t\t// checkCudaErrors(cudaMemAdvise(value_table, sizeof(ValueType) * table_size, cudaMemAdviseSetAccessedBy, dev_id));\n\t\t}\n\t\tvoid um_advise_preferred_loc_init(int dev_id = 0) {\n#\tif DEBUG\n\t\t\tprintf(\"[DEBUG] Setting HashTable_UM_Advice PreferredLocation for Dev %d\\n\", dev_id);\n#\tendif\n\t\t\t// checkCudaErrors(cudaMemAdvise(entry_count, sizeof(int), cudaMemAdviseSetPreferredLocation, dev_id));\n\t\t\t// checkCudaErrors(cudaMemAdvise(key_table, sizeof(KeyType) * table_size, cudaMemAdviseSetPreferredLocation, dev_id));\n\t\t\t// checkCudaErrors(cudaMemAdvise(value_table, sizeof(ValueType) * table_size, cudaMemAdviseSetPreferredLocation, dev_id));\n\t\t}\n#endif\n\t};\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Geometry/GeometrySampler.h", "content": "#ifndef GEOMETRY_SAMPLER_H\n#define GEOMETRY_SAMPLER_H\n#include \n#include \n\n#include \"MnBase/Math/Vec.h\"\n\nnamespace mn {\n\ntemplate\nauto sample_uniform_box(T dx, vec minc, vec maxc) {///< cube\n\tstd::vector> data;\n\n\tfor(int i = minc[0]; i < maxc[0]; ++i) {\n\t\tfor(int j = minc[1]; j < maxc[1]; ++j) {\n\t\t\tfor(int k = minc[2]; k < maxc[2]; ++k) {\n\t\t\t\tstd::array cell_center;\n\t\t\t\tcell_center[0] = (i) *dx;\n\t\t\t\tcell_center[1] = (j) *dx;\n\t\t\t\tcell_center[2] = (k) *dx;\n\n\t\t\t\tfor(int ii = -1; ii <= 1; ii = ii + 2) {\n\t\t\t\t\tfor(int jj = -1; jj <= 1; jj = jj + 2) {\n\t\t\t\t\t\tfor(int kk = -1; kk <= 1; kk = kk + 2) {\n\t\t\t\t\t\t\tstd::array particle;\n\t\t\t\t\t\t\tparticle[0] = cell_center[0] + ii * 0.25 * dx;\n\t\t\t\t\t\t\tparticle[1] = cell_center[1] + jj * 0.25 * dx;\n\t\t\t\t\t\t\tparticle[2] = cell_center[2] + kk * 0.25 * dx;\n\t\t\t\t\t\t\tdata.push_back(particle);\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\treturn data;\n}\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Math/Bit/Bits.h", "content": "#ifndef BITS_H\n#define BITS_H\n#include \n\n#include \n#include \n\nnamespace mn {\n/**\n */\ntemplate\nconstexpr Integer interleaved_bit_mask(int dim) noexcept {\n\tconstexpr Integer UNIT {1};\n\tauto totalBits = sizeof(Integer) << 3;\n\tInteger mask = 0;\n\tfor(decltype(totalBits) curBit = 0; curBit < totalBits; curBit += dim) {\n\t\tmask |= (UNIT << curBit);\n\t}\n\treturn mask;\n}\n/**\n *\t\\fn uint32_t bit_length(uint32_t n)\n *\t\\brief compute the count of significant digits of a number\n *\t\\param N the number\n */\ntemplate\nconstexpr Integer bit_length(Integer n) noexcept {\n\tif(n > 0) {\n\t\treturn bit_length(n >> 1) + static_cast(1);\n\t} else {\n\t\treturn 0;\n\t}\n}\n/**\n *\t\\fn uint32_t bit_count(uint32_t N)\n *\t\\brief compute the count of digits required to express integers in [0,\n *N) \\param N the maximum of the range\n */\ntemplate\nconstexpr Integer bit_count(Integer n) noexcept {\n\tif(n > 0) {\n\t\treturn bit_length(n - 1);\n\t} else {\n\t\treturn Integer {0};\n\t}\n}\n/**\n *\t\\fn uint32_t next_power_of_two(uint32_t i)\n *\t\\brief compute the next power of two bigger than the number i\n *\t\\param i the number\n */\nconstexpr uint32_t next_power_of_two(uint32_t i) noexcept {\n\ti--;\n\ti |= i >> 1;\n\ti |= i >> 2;\n\ti |= i >> 4;\n\ti |= i >> 8;\n\ti |= i >> 16;\n\treturn i + 1;\n}\n\ntemplate\nconstexpr Integer binary_reverse(Integer data, char loc = sizeof(Integer) * 8 - 1) {\n\tif(data == 0) {\n\t\treturn 0;\n\t}\n\treturn ((data & 1) << loc) | binary_reverse(data >> 1, loc - 1);\n}\n\ntemplate\nconstexpr unsigned count_leading_zeros(Integer data) {\n\tunsigned res {0};\n\tdata = binary_reverse(data);\n\tif(data == 0) {\n\t\treturn sizeof(Integer) * 8;\n\t}\n\twhile((data & 1) == 0) {\n\t\tres++;\n\t\tdata >>= 1;\n\t}\n\treturn res;\n}\n\nconstexpr int bit_pack(const uint64_t mask, const uint64_t data) {\n\tuint64_t slresult = 0;\n\tuint64_t& ulresult {slresult};\n\tuint64_t uldata = data;\n\tint count\t\t= 0;\n\tulresult\t\t= 0;\n\n\tuint64_t rmask = binary_reverse(mask);\n\tunsigned char lz {0};\n\n\twhile(rmask) {\n\t\tlz = count_leading_zeros(rmask);\n\t\tuldata >>= lz;\n\t\tulresult <<= 1;\n\t\tcount++;\n\t\tulresult |= (uldata & 1);\n\t\tuldata >>= 1;\n\t\trmask <<= lz + 1;\n\t}\n\tulresult <<= 64 - count;// 64 means 64 bits ... maybe not use a constant 64 ...\n\tulresult = binary_reverse(ulresult);\n\treturn static_cast(slresult);\n}\n\nconstexpr uint64_t bit_spread(const uint64_t mask, const int data) {\n\tuint64_t rmask\t= binary_reverse(mask);\n\tint dat\t\t\t= data;\n\tuint64_t result = 0;\n\tunsigned char lz {0};\n\twhile(rmask) {\n\t\tlz\t = count_leading_zeros(rmask) + 1;\n\t\tresult = result << lz | (dat & 1);\n\t\tdat >>= 1, rmask <<= lz;\n\t}\n\tresult = binary_reverse(result) >> count_leading_zeros(mask);\n\treturn result;\n}\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Math/Bit/SpatialEncoder.cuh", "content": "#ifndef SPATIAL_ENCODER_CUH\n#define SPATIAL_ENCODER_CUH\n#include \n#include \n\n#include \"MnBase/AggregatedAttribs.cuh\"\n#include \"MnBase/Math/Bit/Bits.h\"\n\n#define CHECK_ERRORS 0\n\nnamespace mn {\n\n__forceinline__ __device__ int bit_pack_64(const uint64_t mask, const uint64_t data) {\n\tunion {\n\t\tuint64_t slresult;\n\t\tuint64_t ulresult;\n\t};//FIXME:Why this union? (Both members have the same type)\n\tuint64_t uldata = data;\n\tint count\t\t= 0;\n\tulresult\t\t= 0;\n\n\tuint64_t rmask = __brevll(mask);\n\tunsigned char lz;\n\n\twhile(rmask) {\n\t\tlz = __clzll(rmask);\n\t\tuldata >>= lz;\n\t\tulresult <<= 1;\n\t\tcount++;\n\t\tulresult |= (uldata & 1);\n\t\tuldata >>= 1;\n\t\trmask <<= lz + 1;\n\t}\n\t//NOLINTNEXTLINE(readability-magic-numbers) Define as constant?\n\tulresult <<= 64 - count;// 64 means 64 bits ... maybe not use a constant 64 ...\n\tulresult = __brevll(ulresult);\n\treturn (int) slresult;\n}\n\n__forceinline__ __device__ uint64_t bit_spread_64(const uint64_t mask, const int data) {\n\tuint64_t rmask\t= __brevll(mask);\n\tint dat\t\t\t= data;\n\tuint64_t result = 0;\n\tunsigned char lz, offset = __clzll(rmask);\n\twhile(rmask) {\n\t\tlz\t = __clzll(rmask) + 1;\n\t\tresult = result << lz | (dat & 1);\n\t\tdat >>= 1, rmask <<= lz;\n\t}\n\tresult = __brevll(result) >> __clzll(mask);\n\treturn result;\n}\n\ntemplate\nstruct CoordToOffset {\n\tconst CoordType dx_inv;\n\tstd::array masks;\n\n\tCoordToOffset() = delete;\n\n\t__host__ CoordToOffset(CoordType dxinv, std::array masks)\n\t\t: dx_inv(std::move(dxinv)) {\n\t\tstd::move(masks.begin(), masks.end(), masks);\n\t}\n\n\ttemplate\n\t__forceinline__ __host__ __device__ auto operator()(int dim_no, In&& in) -> MaskType {\n\t\tstatic_assert(std::is_convertible::value, \"CoordToOffset: coordinate type not convertible.\");\n#if CHECK_ERRORS\n\t\tuint64_t res\t\t= bit_spread(masks[dim_no], static_cast(std::forward(in) * static_cast(dx_inv) + static_cast(0.5)) - 1);\n\t\tunsigned pcoordtrue = static_cast(std::forward(in) * static_cast(dx_inv) + static_cast(0.5)) - 1;\n\t\tunsigned pcoord\t\t= bit_pack(masks[dim_no], res);\n\t\tif(pcoord != pcoordtrue) {\n\t\t\tprintf(\"particle's %d-th comp coord(%d)-offset(%u) mapping error!\\n\", dim_no, pcoordtrue, pcoord);\n\t\t}\n#endif\n\t\treturn bit_spread_64(masks[dim_no], static_cast(std::forward(in) * static_cast(dx_inv) + static_cast(0.5)) - 1);\n\t}\n};\n\ntemplate\nstruct OffsetToIndex {\n\tstd::array masks;\n\n\tOffsetToIndex() = delete;\n\n\t__host__ OffsetToIndex(std::array masks) {\n\t\tstd::move(masks.begin(), masks.end(), masks);\n\t}\n\n\ttemplate\n\t__forceinline__ __host__ __device__ auto operator()(int dim_no, MT&& offset) -> IndexType {\n\t\treturn bit_pack_64(masks[dim_no], std::forward(offset));\n\t}\n};\n\ntemplate\nstruct ComputeNeighborKey {\n\tstatic constexpr int DIM = SPGTraits::dimension;\n\n\ttemplate\n\t__forceinline__ __host__ __device__ std::enable_if_t operator()(uint64_t key) {\n\t\tconstexpr uint64_t NEIGHBOR_OFFSET = SPGTraits::neighbor_block_offset((neighborid & 2) != 0 ? 1 : 0, neighborid & 1);\n\n\t\t//printf(\"%d-th neighbor %llx\\n\", neighborid, NEIGHBOR_OFFSET);\n\n\t\tuint64_t x_result = ((key | SPGTraits::MXADD_Xmask) + (NEIGHBOR_OFFSET & ~SPGTraits::MXADD_Xmask)) & ~SPGTraits::MXADD_Xmask;\n\t\tuint64_t y_result = ((key | SPGTraits::MXADD_Ymask) + (NEIGHBOR_OFFSET & ~SPGTraits::MXADD_Ymask)) & ~SPGTraits::MXADD_Ymask;\n\t\tuint64_t w_result = ((key | SPGTraits::MXADD_Wmask) + (NEIGHBOR_OFFSET & ~SPGTraits::MXADD_Wmask)) & ~SPGTraits::MXADD_Wmask;\n\t\tuint64_t result\t = x_result | y_result | w_result;\n\n\t\treturn result >> SPGTraits::page_bits;\n\t}\n\n\ttemplate\n\t__forceinline__ __host__ __device__ std::enable_if_t operator()(uint64_t key) {\n\t\tconstexpr uint64_t NEIGHBOR_OFFSET = SPGTraits::neighbor_block_offset((neighborid & 4) != 0 ? 1 : 0, neighborid & 2 ? 1 : 0, neighborid & 1);\n\n\t\t//printf(\"%d-th neighbor %llx\\n\", neighborid, NEIGHBOR_OFFSET);\n\n\t\tuint64_t x_result = ((key | SPGTraits::MXADD_Xmask) + (NEIGHBOR_OFFSET & ~SPGTraits::MXADD_Xmask)) & ~SPGTraits::MXADD_Xmask;\n\t\tuint64_t y_result = ((key | SPGTraits::MXADD_Ymask) + (NEIGHBOR_OFFSET & ~SPGTraits::MXADD_Ymask)) & ~SPGTraits::MXADD_Ymask;\n\t\tuint64_t z_result = ((key | SPGTraits::MXADD_Zmask) + (NEIGHBOR_OFFSET & ~SPGTraits::MXADD_Zmask)) & ~SPGTraits::MXADD_Zmask;\n\t\tuint64_t w_result = ((key | SPGTraits::MXADD_Wmask) + (NEIGHBOR_OFFSET & ~SPGTraits::MXADD_Wmask)) & ~SPGTraits::MXADD_Wmask;\n\t\tuint64_t result\t = x_result | y_result | z_result | w_result;\n\n\t\treturn result >> SPGTraits::page_bits;\n\t}\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Math/Matrix/EigenDecomposition.cuh", "content": "#ifndef EIGEN_DECOMPOSITION_CUH\n#define EIGEN_DECOMPOSITION_CUH\n\n#include \n\n#include \"MatrixUtils.h\"\n\nnamespace mn {\n\nnamespace math {\n\n\ttemplate\n\t__forceinline__ __device__ void fast_eigenvalues(const std::array& mat, std::array& lambda) {\n\t\t// 24 mults, 20 adds, 1 atan2, 1 sincos, 2 sqrts\n\t\tdouble m\t = (1.0 / 3) * (mat[0] + mat[4] + mat[8]);\n\t\tdouble a00\t = mat[0] - m;\n\t\tdouble a11\t = mat[4] - m;\n\t\tdouble a22\t = mat[8] - m;\n\t\tdouble a12_sqr = mat[3] * mat[3];\n\t\tdouble a13_sqr = mat[6] * mat[6];\n\t\tdouble a23_sqr = mat[7] * mat[7];\n\t\tdouble p\t = (1.0 / 6) * (a00 * a00 + a11 * a11 + a22 * a22 + 2 * (a12_sqr + a13_sqr + a23_sqr));\n\t\tdouble q\t = 0.5 * (a00 * (a11 * a22 - a23_sqr) - a11 * a13_sqr - a22 * a12_sqr) + mat[3] * mat[6] * mat[7];\n\t\tdouble sqrt_p = sqrt(p);\n\t\tdouble disc\t = p * p * p - q * q;\n\t\tdouble phi\t = (1.0 / 3) * atan2(sqrt(fmax(0.0, disc)), q);\n\t\tdouble c = cos(phi), s = sin(phi);\n\t\tdouble sqrt_p_cos\t\t\t = sqrt_p * c;\n\t\tdouble root_three_sqrt_p_sin = sqrt(3.0) * sqrt_p * s;\n\t\tlambda[0]\t\t\t\t\t = m + 2 * sqrt_p_cos;\n\t\tlambda[1]\t\t\t\t\t = m - sqrt_p_cos - root_three_sqrt_p_sin;\n\t\tlambda[2]\t\t\t\t\t = m - sqrt_p_cos + root_three_sqrt_p_sin;\n\t\tif(lambda[0] < lambda[1]) {\n\t\t\tswap(lambda + 0, lambda + 1);\n\t\t}\n\t\tif(lambda[1] < lambda[2]) {\n\t\t\tswap(lambda + 1, lambda + 2);\n\t\t}\n\t\tif(lambda[0] < lambda[1]) {\n\t\t\tswap(lambda + 0, lambda + 1);\n\t\t}\n\t}\n\n\ttemplate\n\t__forceinline__ __device__ void fast_eigenvectors(const std::array& mat, std::array& lambda, std::array vecs) {///< column major assumed\n\t\t// 71 mults, 44 adds, 3 divs, 3 sqrts\n\t\t// flip if necessary so that first eigenvalue is the most different\n\t\tbool flipped\t\t = false;\n\t\tdouble lambda_flip[3] = {lambda[0], lambda[1], lambda[2]};\n\t\tif(lambda[0] - lambda[1] < lambda[1] - lambda[2]) {// 2a\n\t\t\tswap(lambda_flip + 0, lambda_flip + 2);\n\t\t\tflipped = true;\n\t\t}\n\n\t\t// get first eigenvector\n\t\tstd::array c1;\n\t\tstd::array tmp;\n\t\tstd::array dtmp;\n\t\tfor(int i = 0; i < 9; ++i) {\n\t\t\ttmp[i] = mat[i] - (((i & 3) == 0) ? lambda_flip[0] : 0);\n\t\t}\n\t\tmatrixCofactor3d(tmp, c1);\n\t\t// Eigen::Matrix3d::Index i;\n\t\t// T norm2 = c1.colwise().squaredNorm().maxCoeff(&i); // 3a + 12m+6a +\n\t\t// 9m+6a+1d+1s = 21m+15a+1d+1s\n\t\tint i;\n\t\tdtmp[0]\t\t = c1[0] * c1[0] + c1[1] * c1[1] + c1[2] * c1[2];\n\t\tdtmp[1]\t\t = c1[3] * c1[3] + c1[4] * c1[4] + c1[5] * c1[5];\n\t\tdtmp[2]\t\t = c1[6] * c1[6] + c1[7] * c1[7] + c1[8] * c1[8];\n\t\tdouble norm2 = dtmp[0];\n\t\ti\t\t\t = 0;\n\t\tif(dtmp[1] > norm2) {\n\t\t\tnorm2 = dtmp[1];\n\t\t\ti\t = 1;\n\t\t}\n\t\tif(dtmp[2] > norm2) {\n\t\t\tnorm2 = dtmp[2];\n\t\t\ti\t = 2;\n\t\t}\n\n\t\t// Eigen::Vector3d v1;\n\t\tstd::array v1;\n\t\tif(sgn(norm2) > 0) {\n\t\t\tdouble one_over_sqrt = 1.0 / sqrt(norm2);\n\t\t\tfor(int c = 0; c < 3; ++c) {\n\t\t\t\tv1[c] = c1[i * 3 + c] * one_over_sqrt;\n\t\t\t}\n\t\t} else {\n\t\t\tv1[0] = 1;\n\t\t\tv1[1] = 0;\n\t\t\tv1[2] = 0;\n\t\t}\n\n\t\t// form basis for orthogonal complement to v1, and reduce A to this space\n\t\torthogonalVector(v1, tmp);\n\t\tdtmp[3] = tmp[0] * tmp[0] + tmp[1] * tmp[1] + tmp[2] * tmp[2];\n\t\tdtmp[3] = 1.0 / sqrt(dtmp[3]);\n\t\tfor(int i = 0; i < 3; ++i) {\n\t\t\ttmp[i] *= dtmp[3];\n\t\t}\n\t\tstd::array v1_orthogonal = {tmp[0], tmp[1], tmp[2]};// 6m+2a+1d+1s (tweak: 5m+1a+1d+1s)\n\t\t// Eigen::Matrix other_v;\n\t\tstd::array other_v;///< 3x2\n\t\tother_v[0] = v1_orthogonal[0];\n\t\tother_v[1] = v1_orthogonal[1];\n\t\tother_v[2] = v1_orthogonal[2];\n\t\t// other_v.col(1) = v1.cross(v1_orthogonal); // 6m+3a (tweak: 4m+1a)\n\t\tcross(v1, v1_orthogonal, tmp);\n\t\tother_v[3] = tmp[0];\n\t\tother_v[4] = tmp[1];\n\t\tother_v[5] = tmp[2];\n\n\t\t// 2x3\n\t\ttmp[0] = other_v[0] * mat[0] + other_v[1] * mat[1] + other_v[2] * mat[2];\n\t\ttmp[1] = other_v[3] * mat[0] + other_v[4] * mat[1] + other_v[5] * mat[2];\n\t\ttmp[2] = other_v[0] * mat[3] + other_v[1] * mat[4] + other_v[2] * mat[5];\n\t\ttmp[3] = other_v[3] * mat[3] + other_v[4] * mat[4] + other_v[5] * mat[5];\n\t\ttmp[4] = other_v[0] * mat[6] + other_v[1] * mat[7] + other_v[2] * mat[8];\n\t\ttmp[5] = other_v[3] * mat[6] + other_v[4] * mat[7] + other_v[5] * mat[8];\n\n\t\tstd::array A_reduced = {tmp[0] * other_v[0] + tmp[2] * other_v[1] + tmp[4] * other_v[2], tmp[1] * other_v[0] + tmp[3] * other_v[1] + tmp[5] * other_v[2], tmp[0] * other_v[3] + tmp[2] * other_v[4] + tmp[4] * other_v[5], tmp[1] * other_v[3] + tmp[3] * other_v[4] + tmp[5] * other_v[5]};\n\t\t// Eigen::Matrix2d A_reduced = other_v.transpose() * A_Sym * other_v; //\n\t\t// 21m+12a (tweak: 18m+9a)\n\n\t\t// find third eigenvector from A_reduced, and fill in second via cross product\n\t\t// Eigen::Matrix2d c3;\n\t\tstd::array c3;\n\t\t// computeCofactorMtr<2>(A_reduced - lambda_flip(2) *\n\t\t// Eigen::Matrix2d::Identity(), c3);\n\t\tfor(int i = 0; i < 4; ++i) {\n\t\t\ttmp[i] = A_reduced[i] - (((i % 3) == 0) ? lambda_flip[2] : 0);\n\t\t}\n\t\tmatrixCofactor2d(tmp, c3);\n\n\t\tint j;\n\t\t// norm2 = c3.colwise().squaredNorm().maxCoeff(&j); // 3a + 12m+6a +\n\t\t// 9m+6a+1d+1s = 21m+15a+1d+1s\n\t\tdtmp[0] = c3[0] * c3[0] + c3[1] * c3[1];\n\t\tdtmp[1] = c3[2] * c3[2] + c3[3] * c3[3];\n\t\tnorm2\t= dtmp[0];\n\t\tj\t\t= 0;\n\t\tif(dtmp[1] > norm2) {\n\t\t\tnorm2 = dtmp[1];\n\t\t\tj\t = 1;\n\t\t}\n\n\t\tstd::array v3;\n\t\tif(sgn(norm2) > 0) {\n\t\t\tdouble one_over_sqrt = (T) 1 / sqrt(norm2);\n\t\t\tv3[0]\t\t\t\t = (other_v[0] * c3[j * 2 + 0] + other_v[3] * c3[j * 2 + 1]) * one_over_sqrt;\n\t\t\tv3[1]\t\t\t\t = (other_v[1] * c3[j * 2 + 0] + other_v[4] * c3[j * 2 + 1]) * one_over_sqrt;\n\t\t\tv3[2]\t\t\t\t = (other_v[2] * c3[j * 2 + 0] + other_v[5] * c3[j * 2 + 1]) * one_over_sqrt;\n\t\t} else {\n\t\t\tv3[0] = other_v[0];\n\t\t\tv3[1] = other_v[1];\n\t\t\tv3[2] = other_v[2];\n\t\t}\n\n\t\tstd::array v2;\n\t\tcross(v3, v1, v2);\n\t\t// v2 = v3.cross(v1); // 6m+3a\n\t\t// finish\n\t\tif(flipped) {\n\t\t\tvector_copy(1., v3, vecs + 0);\n\t\t\tvector_copy(1., v2, vecs + 3);\n\t\t\tvector_copy(-1., v1, vecs + 6);\n\t\t} else {\n\t\t\tvector_copy(1., v1, vecs + 0);\n\t\t\tvector_copy(1., v2, vecs + 3);\n\t\t\tvector_copy(1., v3, vecs + 6);\n\t\t}\n\t}\n\n\ttemplate\n\t__forceinline__ __device__ void make_pd_3d(const std::array& mat, T eps = 1e-6) {\n\t\tstd::array vals;\n\t\tstd::array vecs;\n\t\tstd::array VT;\n\t\tstd::array tmp;\n\n\t\tfast_eigenvalues(mat, vals);\n\t\tfast_eigenvectors(mat, vals, vecs);\n\t\tfor(int i = 0; i < 3; ++i) {\n\t\t\tvals[i] = vals[i] > eps ? vals[i] : eps;///< clamp\n\t\t}\n\t\tmatrix_transpose_3d(vecs, VT);\n\t\tmatrix_diagonal_matrix_multiplication_3d(vecs, vals, tmp);\n\t\tmatrix_matrix_multiplication_3d(tmp, VT, mat);\n\t}\n\n\ttemplate\n\t__forceinline__ __device__ void make_pd_2d(const std::array& mat, T eps = 1e-6) {\n\t\t// based on\n\t\t// http://www.math.harvard.edu/archive/21b_fall_04/exhibits/2dmatrices/\n\t\tconst double a = mat[0];\n\t\tconst double b = (mat[2] + mat[1]) / 2.0;\n\t\tconst double d = mat[3];\n\n\t\tdouble b2\t\t\t\t= b * b;\n\t\tconst double d_big\t\t= a * d - b2;\n\t\tconst double t_div_2\t= (a + d) / 2.0;\n\t\tconst double sqrt_tt_4d = sqrt(t_div_2 * t_div_2 - d_big);\n\t\tconst double l2\t\t\t= t_div_2 - sqrt_tt_4d;\n\t\tif(l2 < 0.0) {\n\t\t\tconst double l1 = t_div_2 + sqrt_tt_4d;\n\t\t\tif(l1 <= 0.0) {\n\t\t\t\tmat[0] = mat[1] = mat[2] = mat[3] = 0.0;\n\t\t\t} else {\n\t\t\t\tif(b2 == 0.0) {\n\t\t\t\t\tmat[0] = l1;\n\t\t\t\t\tmat[1] = mat[2] = mat[3] = 0.0f;\n\t\t\t\t} else {\n\t\t\t\t\tconst double L1md\t\t = l1 - d;\n\t\t\t\t\tconst double L1md_div_L1 = L1md / l1;\n\t\t\t\t\tmat[0]\t\t\t\t\t = L1md_div_L1 * L1md;\n\t\t\t\t\tmat[1] = mat[2] = b * L1md_div_L1;\n\t\t\t\t\tmat[3]\t\t\t= b2 / l1;\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}// namespace math\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Math/Matrix/Givens.cuh", "content": "/**\nGivens rotation\n*/\n#ifndef GIVENS_CUH\n#define GIVENS_CUH\n#include \n#include \n\n#define ENABLE_COLUMN_ROTATION 0\n#define ENABLE_ADDITIONAL_GIVENS_FUNCTION 0\n\nnamespace mn {\n\n//Stable calculation from https://en.wikipedia.org/wiki/Givens_rotation\nnamespace math {\n\t/**\n\t\t\tClass for givens rotation.\n\t\t\tRow rotation G*A corresponds to something like\n\t\t\tc -s 0\n\t\t\t( s c 0 ) A\n\t\t\t0 0 1\n\t\t\tColumn rotation A G' corresponds to something like\n\t\t\tc -s 0\n\t\t\tA ( s c 0 )\n\t\t\t0 0 1\n\n\t\t\tc and s are always computed so that\n\t\t\t( c -s ) ( a ) = ( * )\n\t\t\ts c b ( 0 )\n\n\t\t\tAssume rowi\n\tstruct GivensRotation {\n\t public:\n\t\tint rowi;\n\t\tint rowk;\n\t\tT c;\n\t\tT s;\n\t\tT r;\n\n\t\t__forceinline__ __host__ __device__ GivensRotation(int rowi_in, int rowk_in)\n\t\t\t: rowi(rowi_in)\n\t\t\t, rowk(rowk_in)\n\t\t\t, c(1)\n\t\t\t, s(0) {}\n\n\t\t__forceinline__ __host__ __device__ GivensRotation(T a, T b, int rowi_in, int rowk_in)\n\t\t\t: rowi(rowi_in)\n\t\t\t, rowk(rowk_in) {\n\t\t\tcompute(a, b);\n\t\t}\n\n\t\t__forceinline__ __host__ __device__ ~GivensRotation() {}\n\n\t\t__forceinline__ __host__ __device__ void set_identity() {\n\t\t\tc = 1;\n\t\t\ts = 0;\n\t\t}\n\n\t\t__forceinline__ __host__ __device__ void transpose_in_place() {\n\t\t\ts = -s;\n\t\t}\n\n\t\t/**\n\t\t\t\tCompute c and s from a and b so that\n\t\t\t\t( c -s ) ( a ) = ( * )\n\t\t\t\ts c b ( 0 )\n\t\t\t\t*/\n\t\ttemplate\n\t\t__forceinline__ __host__ __device__ std::enable_if_t, std::is_same>::value, void> compute(const TT a, const TT b) {\n\t\t\tif(b == 0.0){\n\t\t\t\tif(a == 0.0){\n\t\t\t\t\tc = static_cast(1.0);\n\t\t\t\t}else{\n\t\t\t\t\tc = std::copysign(static_cast(1.0), a);\n\t\t\t\t}\n\t\t\t\ts = 0.0;\n\t\t\t\tr = std::abs(a);\n\t\t\t}else if(a == 0.0){\n\t\t\t\tc = 0.0;\n\t\t\t\ts = std::copysign(static_cast(1.0), b);\n\t\t\t\tr = std::abs(b);\n\t\t\t}else if (std::abs(a) > std::abs(b)){\n\t\t\t\tconst TT t = b / a;\n\t\t\t\tconst TT u = std::copysign(sqrt(static_cast(1.0) + t * t), a);\n\t\t\t\tc = static_cast(1.0) / u;\n\t\t\t\ts = -c * t;\n\t\t\t\tr = a * u;\n\t\t\t}else{\n\t\t\t\tconst TT t = a / b;\n\t\t\t\tconst TT u = std::copysign(sqrt(static_cast(1.0) + t * t), b);\n\t\t\t\ts = -static_cast(1.0) / u;\n\t\t\t\tc = t / u;\n\t\t\t\tr = b * u;\n\t\t\t}\n\t\t}\n\n\t\t/**\n\t\t\t Fill the R with the entries of this rotation\n\t\t\t\t*/\n\t\ttemplate\n\t\t__forceinline__ __host__ __device__ void fill(std::array& a) const {\n\t\t\tfor(int i = 0; i < Dim * Dim; ++i) {\n\t\t\t\ta[i] = 0;\n\t\t\t}\n\t\t\tfor(int i = 0; i < Dim * Dim; i += Dim + 1) {\n\t\t\t\ta[i] = 1;\n\t\t\t}\n\t\t\ta[rowi + rowi * Dim] = c;\n\t\t\ta[rowk + rowi * Dim] = s;\n\t\t\ta[rowi + rowk * Dim] = -s;\n\t\t\ta[rowk + rowk * Dim] = c;\n\t\t}\n\n\t\t/**\n\t\t\t\tThis function does something like Q^T A -> A\n\t\t\t\t[ c -s 0 ]\n\t\t\t\t[ s c 0 ] A -> A\n\t\t\t\t[ 0 0 1 ]\n\t\t\t\tIt only affects row i and row k of A.\n\t\t\t\t*/\n\t\ttemplate\n\t\t__forceinline__ __host__ __device__ void mat_rotation(std::array& a) const {\n\t\t\tfor(int d = 0; d < Dim; d++) {\n\t\t\t\tT1 tau1\t\t\t = a[rowi + d * Dim];\n\t\t\t\tT1 tau2\t\t\t = a[rowk + d * Dim];\n\t\t\t\ta[rowi + d * Dim] = c * tau1 - s * tau2;\n\t\t\t\ta[rowk + d * Dim] = s * tau1 + c * tau2;\n\t\t\t}\n\t\t}\n\n\t\ttemplate\n\t\t__forceinline__ void vec_rotation(std::array& a) const {\n\t\t\tT1 tau1 = a[rowi];\n\t\t\tT1 tau2 = a[rowk];\n\t\t\ta[rowi] = c * tau1 - s * tau2;\n\t\t\ta[rowk] = s * tau1 + c * tau2;\n\t\t}\n\n#if ENABLE_COLUMN_ROTATION\n\t\t/**\n\t\t\t\tThis function does something like A Q -> A\n\t\t\t\t [ c s 0 ]\n\t\t\t\tA [-s c 0 ] -> A\n\t\t\t\t [ 0 0 1 ]\n\t\t\t\tIt only affects column i and column k of A.\n\t\t\t\t*/\n\t\ttemplate\n\t\tZIRAN_FORCE_INLINE void column_rotation(MatrixType& a) const {\n\t\t\tfor(int j = 0; j < a.rows(); j++) {\n\t\t\t\tT tau1\t = a(j, rowi);\n\t\t\t\tT tau2\t = a(j, rowk);\n\t\t\t\ta(j, rowi) = c * tau1 - s * tau2;\n\t\t\t\ta(j, rowk) = s * tau1 + c * tau2;\n\t\t\t}\n\t\t\t//not type safe :/\n\t\t}\n#endif\n\n\t\t/**\n\t\t\t Multiply givens must be for same row and column\n\t\t\t **/\n\t\t__forceinline__ __host__ __device__ void operator*=(const GivensRotation& a) {\n\t\t\tT new_c = c * a.c - s * a.s;\n\t\t\tT new_s = s * a.c + c * a.s;\n\t\t\tc\t\t= new_c;\n\t\t\ts\t\t= new_s;\n\t\t}\n\n\t\t/**\n\t\t\t Multiply givens must be for same row and column\n\t\t\t **/\n\t\t__forceinline__ __host__ __device__ GivensRotation operator*(const GivensRotation& a) const {\n\t\t\tGivensRotation r(*this);\n\t\t\tr *= a;\n\t\t\treturn r;\n\t\t}\n\t};\n\n#if ENABLE_ADDITIONAL_GIVENS_FUNCTION\n\t/**\n\t\t\t\\brief zero chasing the 3X3 matrix to bidiagonal form\n\t\t\toriginal form of H:\n\t\t\tx x 0\n\t\t\tx x x\n\t\t\t0 0 x\n\t\t\tafter zero chase:\n\t\t\tx x 0\n\t\t\t0 x x\n\t\t\t0 0 x\n\t\t\t*/\n\ttemplate\n\tinline ZIRAN_FORCE_INLINE void zero_chase(Matrix& h, Matrix& u, Matrix& v) {\n\t\t/**\n\t\t\t\tReduce H to of form\n\t\t\t\tx x +\n\t\t\t\t0 x x\n\t\t\t\t0 0 x\n\t\t\t\t*/\n\t\tGivensRotation r1(h(0, 0), h(1, 0), 0, 1);\n\t\t/**\n\t\t\t\tReduce H to of form\n\t\t\t\tx x 0\n\t\t\t\t0 x x\n\t\t\t\t0 + x\n\t\t\t\tCan calculate r2 without multiplying by r1 since both entries are in first two\n\t\t\t\trows thus no need to divide by sqrt(a^2+b^2)\n\t\t\t\t*/\n\t\tGivensRotation r2(1, 2);\n\t\tif(h(1, 0) != 0) {\n\t\t\tr2.compute(h(0, 0) * h(0, 1) + h(1, 0) * h(1, 1), h(0, 0) * h(0, 2) + h(1, 0) * h(1, 2));\n\t\t} else {\n\t\t\tr2.compute(h(0, 1), h(0, 2));\n\t\t}\n\n\t\tr1.row_rotation(h);\n\n\t\t/* GivensRotation r2(h(0, 1), h(0, 2), 1, 2); */\n\t\tr2.column_rotation(h);\n\t\tr2.column_rotation(v);\n\n\t\t/**\n\t\t\t\tReduce H to of form\n\t\t\t\tx x 0\n\t\t\t\t0 x x\n\t\t\t\t0 0 x\n\t\t\t\t*/\n\t\tGivensRotation r3(h(1, 1), h(2, 1), 1, 2);\n\t\tr3.row_rotation(h);\n\n\t\t// Save this till end for better cache coherency\n\t\t// r1.row_rotation(u_transpose);\n\t\t// r3.row_rotation(u_transpose);\n\t\tr1.column_rotation(u);\n\t\tr3.column_rotation(u);\n\t}\n\n\t/**\n\t\t\t \\brief make a 3X3 matrix to upper bidiagonal form\n\t\t\t original form of H: x x x\n\t\t\t\t\t\t\t\t x x x\n\t\t\t\t\t\t\t\t x x x\n\t\t\t after zero chase:\n\t\t\t\t\t\t\t\t x x 0\n\t\t\t\t\t\t\t\t 0 x x\n\t\t\t\t\t\t\t\t 0 0 x\n\t\t */\n\ttemplate\n\tinline ZIRAN_FORCE_INLINE void make_upper_bidiag(Matrix& h, Matrix& u, Matrix& v) {\n\t\tu = Matrix::Identity();\n\t\tv = Matrix::Identity();\n\n\t\t/**\n\t\t\t Reduce H to of form\n\t\t\t\t\t\t\t\t x x x\n\t\t\t\t\t\t\t\t x x x\n\t\t\t\t\t\t\t\t 0 x x\n\t\t\t*/\n\n\t\tGivensRotation r(h(1, 0), h(2, 0), 1, 2);\n\t\tr.row_rotation(h);\n\t\t// r.row_rotation(u_transpose);\n\t\tr.column_rotation(u);\n\t\t// zero_chase(h, u_transpose, v);\n\t\tzero_chase(h, u, v);\n\t}\n\n\t/**\n\t\t\t \\brief make a 3X3 matrix to lambda shape\n\t\t\t original form of H: x x x\n\t\t\t * x x x\n\t\t\t * x x x\n\t\t\t after :\n\t\t\t * x 0 0\n\t\t\t * x x 0\n\t\t\t * x 0 x\n\t\t */\n\ttemplate\n\tinline ZIRAN_FORCE_INLINE void make_lambda_shape(Matrix& h, Matrix& u, Matrix& v) {\n\t\tu = Matrix::Identity();\n\t\tv = Matrix::Identity();\n\n\t\t/**\n\t\t\t Reduce H to of form\n\t\t\t * x x 0\n\t\t\t * x x x\n\t\t\t * x x x\n\t\t\t */\n\n\t\tGivensRotation r1(h(0, 1), h(0, 2), 1, 2);\n\t\tr1.column_rotation(h);\n\t\tr1.column_rotation(v);\n\n\t\t/**\n\t\t\t Reduce H to of form\n\t\t\t * x x 0\n\t\t\t * x x 0\n\t\t\t * x x x\n\t\t\t */\n\n\t\tr1.compute_unconventional(h(1, 2), h(2, 2));\n\t\tr1.row_rotation(h);\n\t\tr1.column_rotation(u);\n\n\t\t/**\n\t\t\t Reduce H to of form\n\t\t\t * x x 0\n\t\t\t * x x 0\n\t\t\t * x 0 x\n\t\t\t */\n\n\t\tGivensRotation r2(h(2, 0), h(2, 1), 0, 1);\n\t\tr2.column_rotation(h);\n\t\tr2.column_rotation(v);\n\n\t\t/**\n\t\t\t Reduce H to of form\n\t\t\t * x 0 0\n\t\t\t * x x 0\n\t\t\t * x 0 x\n\t\t\t */\n\t\tr2.compute_unconventional(h(0, 1), h(1, 1));\n\t\tr2.row_rotation(h);\n\t\tr2.column_rotation(u);\n\t}\n#endif\n}// namespace math\n\n}// namespace mn\n\n#endif\n" }, { "path": "Library/MnBase/Math/Matrix/MatrixKernels.cuh", "content": "#ifndef MATRIX_KERNELS_CUH\n#define MATRIX_KERNELS_CUH\n\n#include \n\n#include \"MnBase/AggregatedAttribs.cuh\"\n\nnamespace mn {\n\ntemplate\n__global__ std::enable_if_t set_identity(int num, AttribPort mat) {\n\tuint32_t idx = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(idx >= num) {\n\t\treturn;\n\t}\n\tfor(int c = 0; c < 9; ++c) {\n\t\tmat[c][idx] = (c & 0x3) != 0 ? 0 : 1;\n\t}\n}\n\ntemplate\n__global__ std::enable_if_t set_identity(int num, AttribPort mat) {\n\tuint32_t idx = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(idx >= num) {\n\t\treturn;\n\t}\n\tmat[0][idx] = 1;\n\tmat[1][idx] = 0;\n\tmat[2][idx] = 0;\n\tmat[3][idx] = 1;\n}\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Math/Matrix/MatrixUtils.h", "content": "#ifndef MATRIX_UTILS_H\n#define MATRIX_UTILS_H\n\n#include \"Utility.h\"\n\nnamespace mn {\n\n//TODO: When we have c++20 use std::span\n\n// matrix multiplification\n// return mat1 * diagnal_matrix * mat2^T\n// input diag: only have diagnal entries\ntemplate\nconstexpr void matmul_mat_diag_mat_t_2d(std::array& out, const std::array& mat1, const std::array& diag, const std::array& mat2_t) {\n\tout[0] = mat1[0] * diag[0] * mat2_t[0] + mat1[2] * diag[1] * mat2_t[2];\n\tout[1] = mat1[1] * diag[0] * mat2_t[0] + mat1[3] * diag[1] * mat2_t[2];\n\n\tout[2] = mat1[0] * diag[0] * mat2_t[1] + mat1[2] * diag[1] * mat2_t[3];\n\tout[3] = mat1[1] * diag[0] * mat2_t[1] + mat1[3] * diag[1] * mat2_t[3];\n}\n\n/* matrix indexes\n mat1 | diag | mat2^T\n 0 3 6 | 0 | 0 1 2\n 1 4 7 | 1 | 3 4 5\n 2 5 8 | 2 | 6 7 8\n*/\ntemplate\nconstexpr void matmul_mat_diag_mat_t_3d(std::array& out, const std::array& mat1, const std::array& diag, const std::array& mat2_t) {\n\tout[0] = mat1[0] * diag[0] * mat2_t[0] + mat1[3] * diag[1] * mat2_t[3] + mat1[6] * diag[2] * mat2_t[6];\n\tout[1] = mat1[1] * diag[0] * mat2_t[0] + mat1[4] * diag[1] * mat2_t[3] + mat1[7] * diag[2] * mat2_t[6];\n\tout[2] = mat1[2] * diag[0] * mat2_t[0] + mat1[5] * diag[1] * mat2_t[3] + mat1[8] * diag[2] * mat2_t[6];\n\n\tout[3] = mat1[0] * diag[0] * mat2_t[1] + mat1[3] * diag[1] * mat2_t[4] + mat1[6] * diag[2] * mat2_t[7];\n\tout[4] = mat1[1] * diag[0] * mat2_t[1] + mat1[4] * diag[1] * mat2_t[4] + mat1[7] * diag[2] * mat2_t[7];\n\tout[5] = mat1[2] * diag[0] * mat2_t[1] + mat1[5] * diag[1] * mat2_t[4] + mat1[8] * diag[2] * mat2_t[7];\n\n\tout[6] = mat1[0] * diag[0] * mat2_t[2] + mat1[3] * diag[1] * mat2_t[5] + mat1[6] * diag[2] * mat2_t[8];\n\tout[7] = mat1[1] * diag[0] * mat2_t[2] + mat1[4] * diag[1] * mat2_t[5] + mat1[7] * diag[2] * mat2_t[8];\n\tout[8] = mat1[2] * diag[0] * mat2_t[2] + mat1[5] * diag[1] * mat2_t[5] + mat1[8] * diag[2] * mat2_t[8];\n}\n\n/* out = mat^T * vec */\ntemplate\nconstexpr void mat_t_mul_vec_3d(std::array& out, const std::array& mat, const std::array& vec) {\n\tout[0] = mat[0] * vec[0] + mat[1] * vec[1] + mat[2] * vec[2];\n\tout[1] = mat[3] * vec[0] + mat[4] * vec[1] + mat[5] * vec[2];\n\tout[2] = mat[6] * vec[0] + mat[7] * vec[1] + mat[8] * vec[2];\n}\n\n/* out = a x b (cross product)\n * = {[a]_x} * b */\ntemplate\nconstexpr void vec_cross_mul_vec_3d(std::array& out, const std::array& a, const std::array& b) {\n\tout[0] = a[1] * b[2] + a[2] * b[1];\n\tout[1] = a[2] * b[0] + a[0] * b[2];\n\tout[2] = a[0] * b[1] + a[1] * b[0];\n}\n\ntemplate\nconstexpr void matrix_cofactor_2d(const std::array& x, std::array& cof) {\n\tcof[0] = x[3];\n\tcof[1] = -x[2];\n\tcof[2] = -x[1];\n\tcof[3] = x[0];\n}\n\ntemplate\nconstexpr void matrix_cofactor_3d(const std::array& x, std::array& cof) {\n\tT cofactor11 = x[4] * x[8] - x[7] * x[5];\n\tT cofactor12 = x[7] * x[2] - x[1] * x[8];\n\tT cofactor13 = x[1] * x[5] - x[4] * x[2];\n\tcof[0]\t\t = cofactor11;\n\tcof[1]\t\t = cofactor12;\n\tcof[2]\t\t = cofactor13;\n\tcof[3]\t\t = x[6] * x[5] - x[3] * x[8];\n\tcof[4]\t\t = x[0] * x[8] - x[6] * x[2];\n\tcof[5]\t\t = x[3] * x[2] - x[0] * x[5];\n\tcof[6]\t\t = x[3] * x[7] - x[6] * x[4];\n\tcof[7]\t\t = x[6] * x[1] - x[0] * x[7];\n\tcof[8]\t\t = x[0] * x[4] - x[3] * x[1];\n}\n\n#if 0\ntemplate \nconstexpr void matrix_inverse(const std::array& x, std::array& inv)\n{\n T cofactor11 = x[4] * x[8] - x[7] * x[5];\n\tT cofactor12 = x[7] * x[2] - x[1] * x[8];\n\tT cofactor13 = x[1] * x[5] - x[4] * x[2];\n T determinant = x[0] * cofactor11 + x[3] * cofactor12 + x[6] * cofactor13;\n T s = 1 / determinant;\n inv[0] = s * cofactor11;\n inv[1] = s * cofactor12;\n inv[2] = s * cofactor13;\n inv[3] = s * x[6] * x[5] - s * x[3] * x[8];\n inv[4] = s * x[0] * x[8] - s * x[6] * x[2];\n inv[5] = s * x[3] * x[2] - s * x[0] * x[5];\n inv[6] = s * x[3] * x[7] - s * x[6] * x[4];\n inv[7] = s * x[6] * x[1] - s * x[0] * x[7];\n inv[8] = s * x[0] * x[4] - s * x[3] * x[1];\n}\n#endif\n\ntemplate\nconstexpr T matrix_determinant_3d(const std::array& x) {\n\treturn x[0] * (x[4] * x[8] - x[7] * x[5]) + x[3] * (x[7] * x[2] - x[1] * x[8]) + x[6] * (x[1] * x[5] - x[4] * x[2]);\n}\n\ntemplate\nconstexpr T matrix_determinant_2d(const std::array& x) {\n\treturn x[0] * x[3] - x[1] * x[2];\n}\n\ntemplate\nconstexpr void matrix_transpose_3d(const std::array& x, std::array& transpose) {\n\ttranspose[0] = x[0];\n\ttranspose[1] = x[3];\n\ttranspose[2] = x[6];\n\ttranspose[3] = x[1];\n\ttranspose[4] = x[4];\n\ttranspose[5] = x[7];\n\ttranspose[6] = x[2];\n\ttranspose[7] = x[5];\n\ttranspose[8] = x[8];\n}\n\ntemplate\nconstexpr void matrix_transpose_2d(const std::array& x, std::array& transpose) {\n\ttranspose[0] = x[0];\n\ttranspose[1] = x[2];\n\ttranspose[2] = x[1];\n\ttranspose[3] = x[3];\n}\n\ntemplate\nconstexpr T matrix_trace_3d(const std::array& x) {\n\treturn x[0] + x[4] + x[8];\n}\n\ntemplate\nconstexpr T matrix_trace_2d(const std::array& x) {\n\treturn x[0] + x[3];\n}\n\ntemplate\nconstexpr void matrix_matrix_multiplication_3d(const std::array& a, const std::array& b, std::array& c) {\n\tc[0] = a[0] * b[0] + a[3] * b[1] + a[6] * b[2];\n\tc[1] = a[1] * b[0] + a[4] * b[1] + a[7] * b[2];\n\tc[2] = a[2] * b[0] + a[5] * b[1] + a[8] * b[2];\n\tc[3] = a[0] * b[3] + a[3] * b[4] + a[6] * b[5];\n\tc[4] = a[1] * b[3] + a[4] * b[4] + a[7] * b[5];\n\tc[5] = a[2] * b[3] + a[5] * b[4] + a[8] * b[5];\n\tc[6] = a[0] * b[6] + a[3] * b[7] + a[6] * b[8];\n\tc[7] = a[1] * b[6] + a[4] * b[7] + a[7] * b[8];\n\tc[8] = a[2] * b[6] + a[5] * b[7] + a[8] * b[8];\n}\n\ntemplate\nconstexpr void matrix_matrix_multiplication_2d(const std::array& a, const std::array& b, std::array& c) {\n\tc[0] = a[0] * b[0] + a[2] * b[1];\n\tc[1] = a[1] * b[0] + a[3] * b[1];\n\tc[2] = a[0] * b[2] + a[2] * b[3];\n\tc[3] = a[1] * b[2] + a[3] * b[3];\n}\n\ntemplate\nconstexpr void matrix_diagonal_matrix_multiplication_3d(const std::array& a, const std::array& b, std::array& c) {\n\tc[0] = a[0] * b[0];\n\tc[1] = a[1] * b[0];\n\tc[2] = a[2] * b[0];\n\tc[3] = a[3] * b[1];\n\tc[4] = a[4] * b[1];\n\tc[5] = a[5] * b[1];\n\tc[6] = a[6] * b[2];\n\tc[7] = a[7] * b[2];\n\tc[8] = a[8] * b[2];\n}\n\ntemplate\nconstexpr void matrix_diagonal_matrix_multiplication_2d(const std::array& a, const std::array& b, std::array& c) {\n\tc[0] = a[0] * b[0];\n\tc[1] = a[1] * b[0];\n\tc[2] = a[2] * b[1];\n\tc[3] = a[3] * b[1];\n}\n\ntemplate\nconstexpr void matrix_transpose_matrix_multiplication_3d(const std::array& a, const std::array& b, std::array& c) {\n\tc[0] = a[0] * b[0] + a[1] * b[1] + a[2] * b[2];\n\tc[1] = a[3] * b[0] + a[4] * b[1] + a[5] * b[2];\n\tc[2] = a[6] * b[0] + a[7] * b[1] + a[8] * b[2];\n\tc[3] = a[0] * b[3] + a[1] * b[4] + a[2] * b[5];\n\tc[4] = a[3] * b[3] + a[4] * b[4] + a[5] * b[5];\n\tc[5] = a[6] * b[3] + a[7] * b[4] + a[8] * b[5];\n\tc[6] = a[0] * b[6] + a[1] * b[7] + a[2] * b[8];\n\tc[7] = a[3] * b[6] + a[4] * b[7] + a[5] * b[8];\n\tc[8] = a[6] * b[6] + a[7] * b[7] + a[8] * b[8];\n}\n\ntemplate\nconstexpr void matrix_transpose_matrix_multiplication_2d(const std::array& a, const std::array& b, std::array& c) {\n\tc[0] = a[0] * b[0] + a[1] * b[1];\n\tc[1] = a[2] * b[0] + a[3] * b[1];\n\tc[2] = a[0] * b[2] + a[1] * b[3];\n\tc[3] = a[2] * b[2] + a[3] * b[3];\n}\n\ntemplate\nconstexpr void matrix_vector_multiplication_3d(const std::array& x, const std::array& v, std::array& result) {\n\tresult[0] = x[0] * v[0] + x[3] * v[1] + x[6] * v[2];\n\tresult[1] = x[1] * v[0] + x[4] * v[1] + x[7] * v[2];\n\tresult[2] = x[2] * v[0] + x[5] * v[1] + x[8] * v[2];\n}\n\ntemplate\nconstexpr void matrix_vector_multiplication_2d(const std::array& x, const std::array& v, std::array& result) {\n\tresult[0] = x[0] * v[0] + x[2] * v[1];\n\tresult[1] = x[1] * v[0] + x[3] * v[1];\n}\n\ntemplate\nconstexpr void vector_matrix_multiplication_3d(const std::array& v, const std::array& x, std::array& result) {\n\tresult[0] = x[0] * v[0] + x[1] * v[1] + x[2] * v[2];\n\tresult[1] = x[3] * v[0] + x[4] * v[1] + x[5] * v[2];\n\tresult[2] = x[6] * v[0] + x[7] * v[1] + x[8] * v[2];\n}\n\ntemplate\nconstexpr void vector_matrix_multiplication_2d(const std::array& v, const std::array& x, std::array& result) {\n\tresult[0] = x[0] * v[0] + x[1] * v[1];\n\tresult[1] = x[2] * v[0] + x[3] * v[1];\n}\n\ntemplate\nconstexpr void matrix_matrix_transpose_multiplication_3d(const std::array& a, const std::array& b, std::array& c) {\n\tc[0] = a[0] * b[0] + a[3] * b[3] + a[6] * b[6];\n\tc[1] = a[1] * b[0] + a[4] * b[3] + a[7] * b[6];\n\tc[2] = a[2] * b[0] + a[5] * b[3] + a[8] * b[6];\n\tc[3] = a[0] * b[1] + a[3] * b[4] + a[6] * b[7];\n\tc[4] = a[1] * b[1] + a[4] * b[4] + a[7] * b[7];\n\tc[5] = a[2] * b[1] + a[5] * b[4] + a[8] * b[7];\n\tc[6] = a[0] * b[2] + a[3] * b[5] + a[6] * b[8];\n\tc[7] = a[1] * b[2] + a[4] * b[5] + a[7] * b[8];\n\tc[8] = a[2] * b[2] + a[5] * b[5] + a[8] * b[8];\n}\n\ntemplate\nconstexpr void matrix_matrix_transpose_multiplication_2d(const std::array& a, const std::array& b, std::array& c) {\n\tc[0] = a[0] * b[0] + a[2] * b[2];\n\tc[1] = a[1] * b[0] + a[3] * b[2];\n\tc[2] = a[0] * b[1] + a[2] * b[3];\n\tc[3] = a[1] * b[1] + a[3] * b[3];\n}\n\ntemplate\nconstexpr void matrix_matrix_tranpose_multiplication_3d(const std::array& in, std::array& out) {\n\tout[0] = in[0] * in[0] + in[3] * in[3] + in[6] * in[6];\n\tout[1] = in[1] * in[0] + in[4] * in[3] + in[7] * in[6];\n\tout[2] = in[2] * in[0] + in[5] * in[3] + in[8] * in[6];\n\n\tout[3] = in[0] * in[1] + in[3] * in[4] + in[6] * in[7];\n\tout[4] = in[1] * in[1] + in[4] * in[4] + in[7] * in[7];\n\tout[5] = in[2] * in[1] + in[5] * in[4] + in[8] * in[7];\n\n\tout[6] = in[0] * in[2] + in[3] * in[5] + in[6] * in[8];\n\tout[7] = in[1] * in[2] + in[4] * in[5] + in[7] * in[8];\n\tout[8] = in[2] * in[2] + in[5] * in[5] + in[8] * in[8];\n}\n\ntemplate\nconstexpr void matrix_deviatoric_3d(const std::array& in, std::array& out) {\n\t//FIXME: Rewrote this, cause for some reasons sometimes precision errors occured (Probably compiler bug)\n\t//T trace_in_div_d = (in[0] + in[4] + in[8]) / static_cast(3.0);\n\tout[0] = in[0] * static_cast(2.0 / 3.0) - (in[4] + in[8]) / static_cast(3.0);\n\tout[1] = in[1];\n\tout[2] = in[2];\n\n\tout[3] = in[3];\n\tout[4] = in[4] * static_cast(2.0 / 3.0) - (in[0] + in[8]) / static_cast(3.0);\n\tout[5] = in[5];\n\n\tout[6] = in[6];\n\tout[7] = in[7];\n\tout[8] = in[8] * static_cast(2.0 / 3.0) - (in[0] + in[4]) / static_cast(3.0);\n}\n\n#if 0\ntemplate \nconstexpr T vector_max_component(const std::array& x)\n{\n T tmp = x[0];\n if (tmp < x[1]){\n tmp = x[1];\n\t}\n if (tmp < x[2]){\n tmp = x[2];\n\t}\n return tmp;\n}\n\ntemplate \nconstexpr T vector_magnitude(const std::array& x)\n{\n return sqrtf(x[0] * x[0] + x[1] * x[1] + x[2] * x[2]);\n}\n\ntemplate \nconstexpr void vector_component_max(const std::array& x, const std::array& y, std::array& result)\n{\n for (int v = 0; v < 3; ++v){\n result[v] = x[v] > y[v] ? x[v] : y[v];\n\t}\n}\n\ntemplate \nconstexpr T signed_distance_oriented_box(const std::array& point, const std::array& box_center, const std::array& edges, const std::array& rotation) {\n std::array tmp;\n for (int v = 0; v < 3; ++v){\n tmp[v] = point[v] - box_center[v];\n\t}\n std::array diff;\n matrixvectormultiplication(rotation, tmp, diff);\n std::array phi;\n for (int v = 0; v < 3; ++v){\n phi[v] = (diff[v] > 0 ? diff[v] : -diff[v]) - edges[v] * .5f;\n\t}\n\n if (phi[0] <= 0 && phi[1] <= 0 && phi[2] <= 0){\n return vector_max_component(phi);\n }else {\n T zeros[3] = {0, 0, 0};\n vector_component_max(phi, zeros, diff);\n return vector_magnitude(diff);\n }\n}\n\ntemplate \nconstexpr void quat_cast(std::array& mat, std::array& quat)\n{\n std::array, 3> m;\n for (int i = 0; i < 3; ++i){\n for (int j = 0; j < 3; ++j){\n m[i][j] = mat[i + j * 3];\n\t}\n\t}\n T four_x_squared_minus1 = m[0][0] - m[1][1] - m[2][2];\n T four_y_squared_minus1 = m[1][1] - m[0][0] - m[2][2];\n T four_z_squared_minus1 = m[2][2] - m[0][0] - m[1][1];\n T four_w_squared_minus1 = m[0][0] + m[1][1] + m[2][2];\n\n int biggest_index = 0;\n T four_biggest_squared_minus1 = four_w_squared_minus1;\n if (four_x_squared_minus1 > four_biggest_squared_minus1)\n {\n four_biggest_squared_minus1 = four_x_squared_minus1;\n biggest_index = 1;\n }\n if (four_y_squared_minus1 > four_biggest_squared_minus1)\n {\n four_biggest_squared_minus1 = four_y_squared_minus1;\n biggest_index = 2;\n }\n if (four_z_squared_minus1 > four_biggest_squared_minus1)\n {\n four_biggest_squared_minus1 = four_z_squared_minus1;\n biggest_index = 3;\n }\n\n T biggest_val = sqrt(four_biggest_squared_minus1 + static_cast(1)) * static_cast(0.5);\n T mult = static_cast(0.25) / biggest_val;\n\n switch (biggest_index)\n {\n case 0:\n quat[0] = biggest_val;\n quat[1] = (m[1][2] - m[2][1]) * mult;\n quat[2] = (m[2][0] - m[0][2]) * mult;\n quat[3] = (m[0][1] - m[1][0]) * mult;\n break;\n case 1:\n quat[0] = (m[1][2] - m[2][1]) * mult;\n quat[1] = biggest_val;\n quat[2] = (m[0][1] + m[1][0]) * mult;\n quat[3] = (m[2][0] + m[0][2]) * mult;\n break;\n case 2:\n quat[0] = (m[2][0] - m[0][2]) * mult;\n quat[1] = (m[0][1] + m[1][0]) * mult;\n quat[2] = biggest_val;\n quat[3] = (m[1][2] + m[2][1]) * mult;\n break;\n case 3:\n quat[0] = (m[0][1] - m[1][0]) * mult;\n quat[1] = (m[2][0] + m[0][2]) * mult;\n quat[2] = (m[1][2] + m[2][1]) * mult;\n quat[3] = biggest_val;\n break;\n default: // Silence a -Wswitch-default warning in GCC. Should never actually get here. Assert is just for sanity.\n //assert(false);\n break;\n }\n}\n\ntemplate \nconstexpr void mat3_cast(const std::array& q, std::array& mat)\n{\n T qxx(q[0] * q[0]);\n T qyy(q[1] * q[1]);\n T qzz(q[2] * q[2]);\n T qxz(q[0] * q[2]);\n T qxy(q[0] * q[1]);\n T qyz(q[1] * q[2]);\n T qwx(q[3] * q[0]);\n T qwy(q[3] * q[1]);\n T qwz(q[3] * q[2]);\n\n /*Result[0][0] = */ mat[0] = T(1) - T(2) * (qyy + qzz);\n /*Result[0][1] = */ mat[3] = T(2) * (qxy + qwz);\n /*Result[0][2] = */ mat[6] = T(2) * (qxz - qwy);\n\n /*Result[1][0] = */ mat[1] = T(2) * (qxy - qwz);\n /*Result[1][1] = */ mat[4] = T(1) - T(2) * (qxx + qzz);\n /*Result[1][2] = */ mat[7] = T(2) * (qyz + qwx);\n\n /*Result[2][0] = */ mat[2] = T(2) * (qxz + qwy);\n /*Result[2][1] = */ mat[5] = T(2) * (qyz - qwx);\n /*Result[2][2] = */ mat[8] = T(1) - T(2) * (qxx + qyy);\n}\n#endif\n\n}// namespace mn\n\n#endif\n" }, { "path": "Library/MnBase/Math/Matrix/Utility.h", "content": "#ifndef MATRIX_UTILITY_H\n#define MATRIX_UTILITY_H\n\nnamespace mn {\n\nnamespace math {\n\ttemplate\n\tconstexpr int sgn(const T n) noexcept {\n\t\treturn n < -1e-10 ? -1 : n > 1e-10;\n\t\t// return n < 0.0 ? -1 : n > 0.0;\n\t\t// return n == 0 ? 0 : 1;\n\t}\n\n\ttemplate\n\tconstexpr T abs(const T n) noexcept {\n\t\treturn n > 0 ? n : -n;\n\t}\n\n\ttemplate\n\tconstexpr void orthogonal_vector(const std::array& input, std::array& output) noexcept {\n\t\tT abs_x = abs(input[0]);\n\t\tT abs_y = abs(input[1]);\n\t\tT abs_z = abs(input[2]);\n\t\tif(abs_x < abs_y) {\n\t\t\tif(abs_x < abs_z) {\n\t\t\t\toutput[0] = 0;\n\t\t\t\toutput[1] = input[2];\n\t\t\t\toutput[2] = -input[1];\n\t\t\t} else {\n\t\t\t\toutput[0] = input[1];\n\t\t\t\toutput[1] = -input[0];\n\t\t\t\toutput[2] = 0;\n\t\t\t}\n\t\t} else {\n\t\t\tif(abs_y < abs_z) {\n\t\t\t\toutput[0] = -input[2];\n\t\t\t\toutput[1] = 0;\n\t\t\t\toutput[2] = input[0];\n\t\t\t} else {\n\t\t\t\toutput[0] = input[1];\n\t\t\t\toutput[1] = -input[0];\n\t\t\t\toutput[2] = 0;\n\t\t\t}\n\t\t}\n\t}\n\n\ttemplate\n\tconstexpr void cross(const std::array& operand1, const std::array& operand2, std::array& output) {\n\t\tconst T& x1 = operand1[0];\n\t\tconst T& y1 = operand1[1];\n\t\tconst T& z1 = operand1[2];\n\t\tconst T& x2 = operand2[0];\n\t\tconst T& y2 = operand2[1];\n\t\tconst T& z2 = operand2[2];\n\t\toutput[0]\t= y1 * z2 - y2 * z1;\n\t\toutput[1]\t= x2 * z1 - x1 * z2;\n\t\toutput[2]\t= x1 * y2 - x2 * y1;\n\t}\n\n\ttemplate\n\tconstexpr void vector_copy(const T scale, const std::array& v, std::array& res) {\n\t\tres[0] = v[0] * scale;\n\t\tres[1] = v[1] * scale;\n\t\tres[2] = v[2] * scale;\n\t}\n\n}// namespace math\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Math/Matrix/qr.cuh", "content": "#ifndef QR_CUH\n#define QR_CUH\n#include \"Givens.cuh\"\n\nnamespace mn {\n\nnamespace math {\n\n\t/**\n\t \\brief 2x2 polar decomposition.\n\t \\param[in] A matrix.\n\t \\param[out] R Robustly a rotation matrix in givens form\n\t \\param[out] S_Sym Symmetric. Whole matrix is stored\n\n\t Whole matrix S is stored since its faster to calculate due to simd vectorization\n\t Polar guarantees negative sign is on the small magnitude singular value.\n\t S is guaranteed to be the closest one to identity.\n\t R is guaranteed to be the closest rotation to A.\n\t */\n\ttemplate\n\t__forceinline__ __host__ __device__ void polar_decomposition(const std::array& a, GivensRotation& r, std::array& s) {\n\t\tdouble x[2]\t\t = {a[0] + a[3], a[1] - a[2]};\n\t\tdouble denominator = sqrt(x[0] * x[0] + x[1] * x[1]);\n\t\tr.c\t\t\t\t = (T) 1;\n\t\tr.s\t\t\t\t = (T) 0;\n\t\tif(denominator != 0) {\n\t\t\t/*\n No need to use a tolerance here because x(0) and x(1) always have\n smaller magnitude then denominator, therefore overflow never happens.\n */\n\t\t\tr.c = x[0] / denominator;\n\t\t\tr.s = -x[1] / denominator;\n\t\t}\n\t\tfor(int i = 0; i < 4; ++i) {\n\t\t\ts[i] = a[i];\n\t\t}\n\t\tr.template mat_rotation<2, T>(s);\n\t}\n\n\t/**\n \\brief 2x2 polar decomposition.\n \\param[in] A matrix.\n \\param[out] R Robustly a rotation matrix.\n \\param[out] S_Sym Symmetric. Whole matrix is stored\n\n Whole matrix S is stored since its faster to calculate due to simd vectorization\n Polar guarantees negative sign is on the small magnitude singular value.\n S is guaranteed to be the closest one to identity.\n R is guaranteed to be the closest rotation to A.\n*/\n\ttemplate\n\t__forceinline__ __host__ __device__ void polar_decomposition(const std::array& a, const std::array& r, const std::array& s) {\n\t\tGivensRotation rotation(0, 1);\n\t\tpolar_decomposition(a, rotation, s);\n\t\trotation.fill<2>(R);\n\t}\n\n}// namespace math\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Math/Matrix/svd.cuh", "content": "#ifndef SVD3_CUH\n#define SVD3_CUH\n\n#include \n\n#include \"Utility.h\"\n#include \"math.h\"// CUDA math library\n#include \"qr.cuh\"\n\n#define gone 1065353216\n#define gsine_pi_over_eight 1053028117\n#define gcosine_pi_over_eight 1064076127\n#define gone_half 0.5f\n#define gsmall_number 1.e-12f\n#define gtiny_number 1.e-20f\n#define gfour_gamma_squared 5.8284273147583007813f\n\nnamespace mn {\n\nnamespace math {\n\n\tunion un {\n\t\tfloat f;\n\t\tunsigned int ui;\n\t};\n\n\ttemplate\n\t__forceinline__ __device__ void svd(\n\t\tT a11,\n\t\tT a12,\n\t\tT a13,\n\t\tT a21,\n\t\tT a22,\n\t\tT a23,\n\t\tT a31,\n\t\tT a32,\n\t\tT a33,// input A\n\t\tT& u11,\n\t\tT& u12,\n\t\tT& u13,\n\t\tT& u21,\n\t\tT& u22,\n\t\tT& u23,\n\t\tT& u31,\n\t\tT& u32,\n\t\tT& u33,// output U\n\t\tT& s11,\n\t\t//float &s12, float &s13, float &s21,\n\t\tT& s22,\n\t\t//float &s23, float &s31, float &s32,\n\t\tT& s33,// output S\n\t\tT& v11,\n\t\tT& v12,\n\t\tT& v13,\n\t\tT& v21,\n\t\tT& v22,\n\t\tT& v23,\n\t\tT& v31,\n\t\tT& v32,\n\t\tT& v33// output V\n\t) {\n\t\tun s_a11;\n\t\tun s_a21;\n\t\tun s_a31;\n\t\tun s_a12;\n\t\tun s_a22;\n\t\tun s_a32;\n\t\tun s_a13;\n\t\tun s_a23;\n\t\tun s_a33;\n\t\tun s_u11;\n\t\tun s_u21;\n\t\tun s_u31;\n\t\tun s_u12;\n\t\tun s_u22;\n\t\tun s_u32;\n\t\tun s_u13;\n\t\tun s_u23;\n\t\tun s_u33;\n\t\tun s_v11;\n\t\tun s_v21;\n\t\tun s_v31;\n\t\tun s_v12;\n\t\tun s_v22;\n\t\tun s_v32;\n\t\tun s_v13;\n\t\tun s_v23;\n\t\tun s_v33;\n\t\tun s_c;\n\t\tun s_s;\n\t\tun s_ch;\n\t\tun s_sh;\n\t\tun s_tmp1;\n\t\tun s_tmp2;\n\t\tun s_tmp3;\n\t\tun s_tmp4;\n\t\tun s_tmp5;\n\t\tun s_s11;\n\t\tun s_s21;\n\t\tun s_s31;\n\t\tun s_s22;\n\t\tun s_s32;\n\t\tun s_s33;\n\t\tun s_qvs;\n\t\tun s_qvvx;\n\t\tun s_qvvy;\n\t\tun s_qvvz;\n\n\t\ts_a11.f = a11;\n\t\ts_a12.f = a12;\n\t\ts_a13.f = a13;\n\t\ts_a21.f = a21;\n\t\ts_a22.f = a22;\n\t\ts_a23.f = a23;\n\t\ts_a31.f = a31;\n\t\ts_a32.f = a32;\n\t\ts_a33.f = a33;\n\n\t\t//###########################################################\n\t\t// Compute normal equations matrix\n\t\t//###########################################################\n\n\t\ts_s11.f\t = s_a11.f * s_a11.f;\n\t\ts_tmp1.f = s_a21.f * s_a21.f;\n\t\ts_s11.f\t = __fadd_rn(s_tmp1.f, s_s11.f);\n\t\ts_tmp1.f = s_a31.f * s_a31.f;\n\t\ts_s11.f\t = __fadd_rn(s_tmp1.f, s_s11.f);\n\n\t\ts_s21.f\t = s_a12.f * s_a11.f;\n\t\ts_tmp1.f = s_a22.f * s_a21.f;\n\t\ts_s21.f\t = __fadd_rn(s_tmp1.f, s_s21.f);\n\t\ts_tmp1.f = s_a32.f * s_a31.f;\n\t\ts_s21.f\t = __fadd_rn(s_tmp1.f, s_s21.f);\n\n\t\ts_s31.f\t = s_a13.f * s_a11.f;\n\t\ts_tmp1.f = s_a23.f * s_a21.f;\n\t\ts_s31.f\t = __fadd_rn(s_tmp1.f, s_s31.f);\n\t\ts_tmp1.f = s_a33.f * s_a31.f;\n\t\ts_s31.f\t = __fadd_rn(s_tmp1.f, s_s31.f);\n\n\t\ts_s22.f\t = s_a12.f * s_a12.f;\n\t\ts_tmp1.f = s_a22.f * s_a22.f;\n\t\ts_s22.f\t = __fadd_rn(s_tmp1.f, s_s22.f);\n\t\ts_tmp1.f = s_a32.f * s_a32.f;\n\t\ts_s22.f\t = __fadd_rn(s_tmp1.f, s_s22.f);\n\n\t\ts_s32.f\t = s_a13.f * s_a12.f;\n\t\ts_tmp1.f = s_a23.f * s_a22.f;\n\t\ts_s32.f\t = __fadd_rn(s_tmp1.f, s_s32.f);\n\t\ts_tmp1.f = s_a33.f * s_a32.f;\n\t\ts_s32.f\t = __fadd_rn(s_tmp1.f, s_s32.f);\n\n\t\ts_s33.f\t = s_a13.f * s_a13.f;\n\t\ts_tmp1.f = s_a23.f * s_a23.f;\n\t\ts_s33.f\t = __fadd_rn(s_tmp1.f, s_s33.f);\n\t\ts_tmp1.f = s_a33.f * s_a33.f;\n\t\ts_s33.f\t = __fadd_rn(s_tmp1.f, s_s33.f);\n\n\t\ts_qvs.f\t = 1.f;\n\t\ts_qvvx.f = 0.f;\n\t\ts_qvvy.f = 0.f;\n\t\ts_qvvz.f = 0.f;\n\n\t\t//###########################################################\n\t\t// Solve symmetric eigenproblem using Jacobi iteration\n\t\t//###########################################################\n\t\tfor(int i = 0; i < 4; i++) {\n\t\t\ts_sh.f\t = s_s21.f * 0.5f;\n\t\t\ts_tmp5.f = __fsub_rn(s_s11.f, s_s22.f);\n\n\t\t\ts_tmp2.f = s_sh.f * s_sh.f;\n\t\t\ts_tmp1.ui = (s_tmp2.f >= gtiny_number) ? 0xffffffff : 0;\n\t\t\ts_sh.ui\t = s_tmp1.ui & s_sh.ui;\n\t\t\ts_ch.ui\t = s_tmp1.ui & s_tmp5.ui;\n\t\t\ts_tmp2.ui = ~s_tmp1.ui & gone;\n\t\t\ts_ch.ui\t = s_ch.ui | s_tmp2.ui;\n\n\t\t\ts_tmp1.f = s_sh.f * s_sh.f;\n\t\t\ts_tmp2.f = s_ch.f * s_ch.f;\n\t\t\ts_tmp3.f = __fadd_rn(s_tmp1.f, s_tmp2.f);\n\t\t\ts_tmp4.f = __frsqrt_rn(s_tmp3.f);\n\n\t\t\ts_sh.f\t = s_tmp4.f * s_sh.f;\n\t\t\ts_ch.f\t = s_tmp4.f * s_ch.f;\n\t\t\ts_tmp1.f = gfour_gamma_squared * s_tmp1.f;\n\t\t\ts_tmp1.ui = (s_tmp2.f <= s_tmp1.f) ? 0xffffffff : 0;\n\n\t\t\ts_tmp2.ui = gsine_pi_over_eight & s_tmp1.ui;\n\t\t\ts_sh.ui\t = ~s_tmp1.ui & s_sh.ui;\n\t\t\ts_sh.ui\t = s_sh.ui | s_tmp2.ui;\n\t\t\ts_tmp2.ui = gcosine_pi_over_eight & s_tmp1.ui;\n\t\t\ts_ch.ui\t = ~s_tmp1.ui & s_ch.ui;\n\t\t\ts_ch.ui\t = s_ch.ui | s_tmp2.ui;\n\n\t\t\ts_tmp1.f = s_sh.f * s_sh.f;\n\t\t\ts_tmp2.f = s_ch.f * s_ch.f;\n\t\t\ts_c.f\t = __fsub_rn(s_tmp2.f, s_tmp1.f);\n\t\t\ts_s.f\t = s_ch.f * s_sh.f;\n\t\t\ts_s.f\t = __fadd_rn(s_s.f, s_s.f);\n\n#ifdef DEBUG_JACOBI_CONJUGATE\n\t\t\tprintf(\"GPU s %.20g, c %.20g, sh %.20g, ch %.20g\\n\", s_s.f, s_c.f, s_sh.f, s_ch.f);\n#endif\n\t\t\t//###########################################################\n\t\t\t// Perform the actual Givens conjugation\n\t\t\t//###########################################################\n\n\t\t\ts_tmp3.f = __fadd_rn(s_tmp1.f, s_tmp2.f);\n\t\t\ts_s33.f\t = s_s33.f * s_tmp3.f;\n\t\t\ts_s31.f\t = s_s31.f * s_tmp3.f;\n\t\t\ts_s32.f\t = s_s32.f * s_tmp3.f;\n\t\t\ts_s33.f\t = s_s33.f * s_tmp3.f;\n\n\t\t\ts_tmp1.f = s_s.f * s_s31.f;\n\t\t\ts_tmp2.f = s_s.f * s_s32.f;\n\t\t\ts_s31.f\t = s_c.f * s_s31.f;\n\t\t\ts_s32.f\t = s_c.f * s_s32.f;\n\t\t\ts_s31.f\t = __fadd_rn(s_tmp2.f, s_s31.f);\n\t\t\ts_s32.f\t = __fsub_rn(s_s32.f, s_tmp1.f);\n\n\t\t\ts_tmp2.f = s_s.f * s_s.f;\n\t\t\ts_tmp1.f = s_s22.f * s_tmp2.f;\n\t\t\ts_tmp3.f = s_s11.f * s_tmp2.f;\n\t\t\ts_tmp4.f = s_c.f * s_c.f;\n\t\t\ts_s11.f\t = s_s11.f * s_tmp4.f;\n\t\t\ts_s22.f\t = s_s22.f * s_tmp4.f;\n\t\t\ts_s11.f\t = __fadd_rn(s_s11.f, s_tmp1.f);\n\t\t\ts_s22.f\t = __fadd_rn(s_s22.f, s_tmp3.f);\n\t\t\ts_tmp4.f = __fsub_rn(s_tmp4.f, s_tmp2.f);\n\t\t\ts_tmp2.f = __fadd_rn(s_s21.f, s_s21.f);\n\t\t\ts_s21.f\t = s_s21.f * s_tmp4.f;\n\t\t\ts_tmp4.f = s_c.f * s_s.f;\n\t\t\ts_tmp2.f = s_tmp2.f * s_tmp4.f;\n\t\t\ts_tmp5.f = s_tmp5.f * s_tmp4.f;\n\t\t\ts_s11.f\t = __fadd_rn(s_s11.f, s_tmp2.f);\n\t\t\ts_s21.f\t = __fsub_rn(s_s21.f, s_tmp5.f);\n\t\t\ts_s22.f\t = __fsub_rn(s_s22.f, s_tmp2.f);\n\n#ifdef DEBUG_JACOBI_CONJUGATE\n\t\t\tprintf(\"%.20g\\n\", s_s11.f);\n\t\t\tprintf(\"%.20g %.20g\\n\", s_s21.f, s_s22.f);\n\t\t\tprintf(\"%.20g %.20g %.20g\\n\", s_s31.f, s_s32.f, s_s33.f);\n#endif\n\n\t\t\t//###########################################################\n\t\t\t// Compute the cumulative rotation, in quaternion form\n\t\t\t//###########################################################\n\n\t\t\ts_tmp1.f = s_sh.f * s_qvvx.f;\n\t\t\ts_tmp2.f = s_sh.f * s_qvvy.f;\n\t\t\ts_tmp3.f = s_sh.f * s_qvvz.f;\n\t\t\ts_sh.f\t = s_sh.f * s_qvs.f;\n\n\t\t\ts_qvs.f\t = s_ch.f * s_qvs.f;\n\t\t\ts_qvvx.f = s_ch.f * s_qvvx.f;\n\t\t\ts_qvvy.f = s_ch.f * s_qvvy.f;\n\t\t\ts_qvvz.f = s_ch.f * s_qvvz.f;\n\n\t\t\ts_qvvz.f = __fadd_rn(s_qvvz.f, s_sh.f);\n\t\t\ts_qvs.f\t = __fsub_rn(s_qvs.f, s_tmp3.f);\n\t\t\ts_qvvx.f = __fadd_rn(s_qvvx.f, s_tmp2.f);\n\t\t\ts_qvvy.f = __fsub_rn(s_qvvy.f, s_tmp1.f);\n\n#ifdef DEBUG_JACOBI_CONJUGATE\n\t\t\tprintf(\"GPU q %.20g %.20g %.20g %.20g\\n\", s_qvvx.f, s_qvvy.f, s_qvvz.f, s_qvs.f);\n#endif\n\n\t\t\t//////////////////////////////////////////////////////////////////////////\n\t\t\t// (1->3)\n\t\t\t//////////////////////////////////////////////////////////////////////////\n\t\t\ts_sh.f\t = s_s32.f * 0.5f;\n\t\t\ts_tmp5.f = __fsub_rn(s_s22.f, s_s33.f);\n\n\t\t\ts_tmp2.f = s_sh.f * s_sh.f;\n\t\t\ts_tmp1.ui = (s_tmp2.f >= gtiny_number) ? 0xffffffff : 0;\n\t\t\ts_sh.ui\t = s_tmp1.ui & s_sh.ui;\n\t\t\ts_ch.ui\t = s_tmp1.ui & s_tmp5.ui;\n\t\t\ts_tmp2.ui = ~s_tmp1.ui & gone;\n\t\t\ts_ch.ui\t = s_ch.ui | s_tmp2.ui;\n\n\t\t\ts_tmp1.f = s_sh.f * s_sh.f;\n\t\t\ts_tmp2.f = s_ch.f * s_ch.f;\n\t\t\ts_tmp3.f = __fadd_rn(s_tmp1.f, s_tmp2.f);\n\t\t\ts_tmp4.f = __frsqrt_rn(s_tmp3.f);\n\n\t\t\ts_sh.f\t = s_tmp4.f * s_sh.f;\n\t\t\ts_ch.f\t = s_tmp4.f * s_ch.f;\n\t\t\ts_tmp1.f = gfour_gamma_squared * s_tmp1.f;\n\t\t\ts_tmp1.ui = (s_tmp2.f <= s_tmp1.f) ? 0xffffffff : 0;\n\n\t\t\ts_tmp2.ui = gsine_pi_over_eight & s_tmp1.ui;\n\t\t\ts_sh.ui\t = ~s_tmp1.ui & s_sh.ui;\n\t\t\ts_sh.ui\t = s_sh.ui | s_tmp2.ui;\n\t\t\ts_tmp2.ui = gcosine_pi_over_eight & s_tmp1.ui;\n\t\t\ts_ch.ui\t = ~s_tmp1.ui & s_ch.ui;\n\t\t\ts_ch.ui\t = s_ch.ui | s_tmp2.ui;\n\n\t\t\ts_tmp1.f = s_sh.f * s_sh.f;\n\t\t\ts_tmp2.f = s_ch.f * s_ch.f;\n\t\t\ts_c.f\t = __fsub_rn(s_tmp2.f, s_tmp1.f);\n\t\t\ts_s.f\t = s_ch.f * s_sh.f;\n\t\t\ts_s.f\t = __fadd_rn(s_s.f, s_s.f);\n\n#ifdef DEBUG_JACOBI_CONJUGATE\n\t\t\tprintf(\"GPU s %.20g, c %.20g, sh %.20g, ch %.20g\\n\", s_s.f, s_c.f, s_sh.f, s_ch.f);\n#endif\n\n\t\t\t//###########################################################\n\t\t\t// Perform the actual Givens conjugation\n\t\t\t//###########################################################\n\n\t\t\ts_tmp3.f = __fadd_rn(s_tmp1.f, s_tmp2.f);\n\t\t\ts_s11.f\t = s_s11.f * s_tmp3.f;\n\t\t\ts_s21.f\t = s_s21.f * s_tmp3.f;\n\t\t\ts_s31.f\t = s_s31.f * s_tmp3.f;\n\t\t\ts_s11.f\t = s_s11.f * s_tmp3.f;\n\n\t\t\ts_tmp1.f = s_s.f * s_s21.f;\n\t\t\ts_tmp2.f = s_s.f * s_s31.f;\n\t\t\ts_s21.f\t = s_c.f * s_s21.f;\n\t\t\ts_s31.f\t = s_c.f * s_s31.f;\n\t\t\ts_s21.f\t = __fadd_rn(s_tmp2.f, s_s21.f);\n\t\t\ts_s31.f\t = __fsub_rn(s_s31.f, s_tmp1.f);\n\n\t\t\ts_tmp2.f = s_s.f * s_s.f;\n\t\t\ts_tmp1.f = s_s33.f * s_tmp2.f;\n\t\t\ts_tmp3.f = s_s22.f * s_tmp2.f;\n\t\t\ts_tmp4.f = s_c.f * s_c.f;\n\t\t\ts_s22.f\t = s_s22.f * s_tmp4.f;\n\t\t\ts_s33.f\t = s_s33.f * s_tmp4.f;\n\t\t\ts_s22.f\t = __fadd_rn(s_s22.f, s_tmp1.f);\n\t\t\ts_s33.f\t = __fadd_rn(s_s33.f, s_tmp3.f);\n\t\t\ts_tmp4.f = __fsub_rn(s_tmp4.f, s_tmp2.f);\n\t\t\ts_tmp2.f = __fadd_rn(s_s32.f, s_s32.f);\n\t\t\ts_s32.f\t = s_s32.f * s_tmp4.f;\n\t\t\ts_tmp4.f = s_c.f * s_s.f;\n\t\t\ts_tmp2.f = s_tmp2.f * s_tmp4.f;\n\t\t\ts_tmp5.f = s_tmp5.f * s_tmp4.f;\n\t\t\ts_s22.f\t = __fadd_rn(s_s22.f, s_tmp2.f);\n\t\t\ts_s32.f\t = __fsub_rn(s_s32.f, s_tmp5.f);\n\t\t\ts_s33.f\t = __fsub_rn(s_s33.f, s_tmp2.f);\n\n#ifdef DEBUG_JACOBI_CONJUGATE\n\t\t\tprintf(\"%.20g\\n\", s_s11.f);\n\t\t\tprintf(\"%.20g %.20g\\n\", s_s21.f, s_s22.f);\n\t\t\tprintf(\"%.20g %.20g %.20g\\n\", s_s31.f, s_s32.f, s_s33.f);\n#endif\n\n\t\t\t//###########################################################\n\t\t\t// Compute the cumulative rotation, in quaternion form\n\t\t\t//###########################################################\n\n\t\t\ts_tmp1.f = s_sh.f * s_qvvx.f;\n\t\t\ts_tmp2.f = s_sh.f * s_qvvy.f;\n\t\t\ts_tmp3.f = s_sh.f * s_qvvz.f;\n\t\t\ts_sh.f\t = s_sh.f * s_qvs.f;\n\n\t\t\ts_qvs.f\t = s_ch.f * s_qvs.f;\n\t\t\ts_qvvx.f = s_ch.f * s_qvvx.f;\n\t\t\ts_qvvy.f = s_ch.f * s_qvvy.f;\n\t\t\ts_qvvz.f = s_ch.f * s_qvvz.f;\n\n\t\t\ts_qvvx.f = __fadd_rn(s_qvvx.f, s_sh.f);\n\t\t\ts_qvs.f\t = __fsub_rn(s_qvs.f, s_tmp1.f);\n\t\t\ts_qvvy.f = __fadd_rn(s_qvvy.f, s_tmp3.f);\n\t\t\ts_qvvz.f = __fsub_rn(s_qvvz.f, s_tmp2.f);\n\n#ifdef DEBUG_JACOBI_CONJUGATE\n\t\t\tprintf(\"GPU q %.20g %.20g %.20g %.20g\\n\", s_qvvx.f, s_qvvy.f, s_qvvz.f, s_qvs.f);\n#endif\n#if 1\n\t\t\t//////////////////////////////////////////////////////////////////////////\n\t\t\t// 1 -> 2\n\t\t\t//////////////////////////////////////////////////////////////////////////\n\n\t\t\ts_sh.f\t = s_s31.f * 0.5f;\n\t\t\ts_tmp5.f = __fsub_rn(s_s33.f, s_s11.f);\n\n\t\t\ts_tmp2.f = s_sh.f * s_sh.f;\n\t\t\ts_tmp1.ui = (s_tmp2.f >= gtiny_number) ? 0xffffffff : 0;\n\t\t\ts_sh.ui\t = s_tmp1.ui & s_sh.ui;\n\t\t\ts_ch.ui\t = s_tmp1.ui & s_tmp5.ui;\n\t\t\ts_tmp2.ui = ~s_tmp1.ui & gone;\n\t\t\ts_ch.ui\t = s_ch.ui | s_tmp2.ui;\n\n\t\t\ts_tmp1.f = s_sh.f * s_sh.f;\n\t\t\ts_tmp2.f = s_ch.f * s_ch.f;\n\t\t\ts_tmp3.f = __fadd_rn(s_tmp1.f, s_tmp2.f);\n\t\t\ts_tmp4.f = __frsqrt_rn(s_tmp3.f);\n\n\t\t\ts_sh.f\t = s_tmp4.f * s_sh.f;\n\t\t\ts_ch.f\t = s_tmp4.f * s_ch.f;\n\t\t\ts_tmp1.f = gfour_gamma_squared * s_tmp1.f;\n\t\t\ts_tmp1.ui = (s_tmp2.f <= s_tmp1.f) ? 0xffffffff : 0;\n\n\t\t\ts_tmp2.ui = gsine_pi_over_eight & s_tmp1.ui;\n\t\t\ts_sh.ui\t = ~s_tmp1.ui & s_sh.ui;\n\t\t\ts_sh.ui\t = s_sh.ui | s_tmp2.ui;\n\t\t\ts_tmp2.ui = gcosine_pi_over_eight & s_tmp1.ui;\n\t\t\ts_ch.ui\t = ~s_tmp1.ui & s_ch.ui;\n\t\t\ts_ch.ui\t = s_ch.ui | s_tmp2.ui;\n\n\t\t\ts_tmp1.f = s_sh.f * s_sh.f;\n\t\t\ts_tmp2.f = s_ch.f * s_ch.f;\n\t\t\ts_c.f\t = __fsub_rn(s_tmp2.f, s_tmp1.f);\n\t\t\ts_s.f\t = s_ch.f * s_sh.f;\n\t\t\ts_s.f\t = __fadd_rn(s_s.f, s_s.f);\n\n#\tifdef DEBUG_JACOBI_CONJUGATE\n\t\t\tprintf(\"GPU s %.20g, c %.20g, sh %.20g, ch %.20g\\n\", s_s.f, s_c.f, s_sh.f, s_ch.f);\n#\tendif\n\n\t\t\t//###########################################################\n\t\t\t// Perform the actual Givens conjugation\n\t\t\t//###########################################################\n\n\t\t\ts_tmp3.f = __fadd_rn(s_tmp1.f, s_tmp2.f);\n\t\t\ts_s22.f\t = s_s22.f * s_tmp3.f;\n\t\t\ts_s32.f\t = s_s32.f * s_tmp3.f;\n\t\t\ts_s21.f\t = s_s21.f * s_tmp3.f;\n\t\t\ts_s22.f\t = s_s22.f * s_tmp3.f;\n\n\t\t\ts_tmp1.f = s_s.f * s_s32.f;\n\t\t\ts_tmp2.f = s_s.f * s_s21.f;\n\t\t\ts_s32.f\t = s_c.f * s_s32.f;\n\t\t\ts_s21.f\t = s_c.f * s_s21.f;\n\t\t\ts_s32.f\t = __fadd_rn(s_tmp2.f, s_s32.f);\n\t\t\ts_s21.f\t = __fsub_rn(s_s21.f, s_tmp1.f);\n\n\t\t\ts_tmp2.f = s_s.f * s_s.f;\n\t\t\ts_tmp1.f = s_s11.f * s_tmp2.f;\n\t\t\ts_tmp3.f = s_s33.f * s_tmp2.f;\n\t\t\ts_tmp4.f = s_c.f * s_c.f;\n\t\t\ts_s33.f\t = s_s33.f * s_tmp4.f;\n\t\t\ts_s11.f\t = s_s11.f * s_tmp4.f;\n\t\t\ts_s33.f\t = __fadd_rn(s_s33.f, s_tmp1.f);\n\t\t\ts_s11.f\t = __fadd_rn(s_s11.f, s_tmp3.f);\n\t\t\ts_tmp4.f = __fsub_rn(s_tmp4.f, s_tmp2.f);\n\t\t\ts_tmp2.f = __fadd_rn(s_s31.f, s_s31.f);\n\t\t\ts_s31.f\t = s_s31.f * s_tmp4.f;\n\t\t\ts_tmp4.f = s_c.f * s_s.f;\n\t\t\ts_tmp2.f = s_tmp2.f * s_tmp4.f;\n\t\t\ts_tmp5.f = s_tmp5.f * s_tmp4.f;\n\t\t\ts_s33.f\t = __fadd_rn(s_s33.f, s_tmp2.f);\n\t\t\ts_s31.f\t = __fsub_rn(s_s31.f, s_tmp5.f);\n\t\t\ts_s11.f\t = __fsub_rn(s_s11.f, s_tmp2.f);\n\n#\tifdef DEBUG_JACOBI_CONJUGATE\n\t\t\tprintf(\"%.20g\\n\", s_s11.f);\n\t\t\tprintf(\"%.20g %.20g\\n\", s_s21.f, s_s22.f);\n\t\t\tprintf(\"%.20g %.20g %.20g\\n\", s_s31.f, s_s32.f, s_s33.f);\n#\tendif\n\n\t\t\t//###########################################################\n\t\t\t// Compute the cumulative rotation, in quaternion form\n\t\t\t//###########################################################\n\n\t\t\ts_tmp1.f = s_sh.f * s_qvvx.f;\n\t\t\ts_tmp2.f = s_sh.f * s_qvvy.f;\n\t\t\ts_tmp3.f = s_sh.f * s_qvvz.f;\n\t\t\ts_sh.f\t = s_sh.f * s_qvs.f;\n\n\t\t\ts_qvs.f\t = s_ch.f * s_qvs.f;\n\t\t\ts_qvvx.f = s_ch.f * s_qvvx.f;\n\t\t\ts_qvvy.f = s_ch.f * s_qvvy.f;\n\t\t\ts_qvvz.f = s_ch.f * s_qvvz.f;\n\n\t\t\ts_qvvy.f = __fadd_rn(s_qvvy.f, s_sh.f);\n\t\t\ts_qvs.f\t = __fsub_rn(s_qvs.f, s_tmp2.f);\n\t\t\ts_qvvz.f = __fadd_rn(s_qvvz.f, s_tmp1.f);\n\t\t\ts_qvvx.f = __fsub_rn(s_qvvx.f, s_tmp3.f);\n#endif\n\t\t}\n\n\t\t//###########################################################\n\t\t// Normalize quaternion for matrix V\n\t\t//###########################################################\n\n\t\ts_tmp2.f = s_qvs.f * s_qvs.f;\n\t\ts_tmp1.f = s_qvvx.f * s_qvvx.f;\n\t\ts_tmp2.f = __fadd_rn(s_tmp1.f, s_tmp2.f);\n\t\ts_tmp1.f = s_qvvy.f * s_qvvy.f;\n\t\ts_tmp2.f = __fadd_rn(s_tmp1.f, s_tmp2.f);\n\t\ts_tmp1.f = s_qvvz.f * s_qvvz.f;\n\t\ts_tmp2.f = __fadd_rn(s_tmp1.f, s_tmp2.f);\n\n\t\ts_tmp1.f = __frsqrt_rn(s_tmp2.f);\n\t\ts_tmp4.f = s_tmp1.f * 0.5f;\n\t\ts_tmp3.f = s_tmp1.f * s_tmp4.f;\n\t\ts_tmp3.f = s_tmp1.f * s_tmp3.f;\n\t\ts_tmp3.f = s_tmp2.f * s_tmp3.f;\n\t\ts_tmp1.f = __fadd_rn(s_tmp1.f, s_tmp4.f);\n\t\ts_tmp1.f = __fsub_rn(s_tmp1.f, s_tmp3.f);\n\n\t\ts_qvs.f\t = s_qvs.f * s_tmp1.f;\n\t\ts_qvvx.f = s_qvvx.f * s_tmp1.f;\n\t\ts_qvvy.f = s_qvvy.f * s_tmp1.f;\n\t\ts_qvvz.f = s_qvvz.f * s_tmp1.f;\n\n\t\t//###########################################################\n\t\t// Transform quaternion to matrix V\n\t\t//###########################################################\n\n\t\ts_tmp1.f = s_qvvx.f * s_qvvx.f;\n\t\ts_tmp2.f = s_qvvy.f * s_qvvy.f;\n\t\ts_tmp3.f = s_qvvz.f * s_qvvz.f;\n\t\ts_v11.f\t = s_qvs.f * s_qvs.f;\n\t\ts_v22.f\t = __fsub_rn(s_v11.f, s_tmp1.f);\n\t\ts_v33.f\t = __fsub_rn(s_v22.f, s_tmp2.f);\n\t\ts_v33.f\t = __fadd_rn(s_v33.f, s_tmp3.f);\n\t\ts_v22.f\t = __fadd_rn(s_v22.f, s_tmp2.f);\n\t\ts_v22.f\t = __fsub_rn(s_v22.f, s_tmp3.f);\n\t\ts_v11.f\t = __fadd_rn(s_v11.f, s_tmp1.f);\n\t\ts_v11.f\t = __fsub_rn(s_v11.f, s_tmp2.f);\n\t\ts_v11.f\t = __fsub_rn(s_v11.f, s_tmp3.f);\n\t\ts_tmp1.f = __fadd_rn(s_qvvx.f, s_qvvx.f);\n\t\ts_tmp2.f = __fadd_rn(s_qvvy.f, s_qvvy.f);\n\t\ts_tmp3.f = __fadd_rn(s_qvvz.f, s_qvvz.f);\n\t\ts_v32.f\t = s_qvs.f * s_tmp1.f;\n\t\ts_v13.f\t = s_qvs.f * s_tmp2.f;\n\t\ts_v21.f\t = s_qvs.f * s_tmp3.f;\n\t\ts_tmp1.f = s_qvvy.f * s_tmp1.f;\n\t\ts_tmp2.f = s_qvvz.f * s_tmp2.f;\n\t\ts_tmp3.f = s_qvvx.f * s_tmp3.f;\n\t\ts_v12.f\t = __fsub_rn(s_tmp1.f, s_v21.f);\n\t\ts_v23.f\t = __fsub_rn(s_tmp2.f, s_v32.f);\n\t\ts_v31.f\t = __fsub_rn(s_tmp3.f, s_v13.f);\n\t\ts_v21.f\t = __fadd_rn(s_tmp1.f, s_v21.f);\n\t\ts_v32.f\t = __fadd_rn(s_tmp2.f, s_v32.f);\n\t\ts_v13.f\t = __fadd_rn(s_tmp3.f, s_v13.f);\n\n\t\t///###########################################################\n\t\t// Multiply (from the right) with V\n\t\t//###########################################################\n\n\t\ts_tmp2.f = s_a12.f;\n\t\ts_tmp3.f = s_a13.f;\n\t\ts_a12.f\t = s_v12.f * s_a11.f;\n\t\ts_a13.f\t = s_v13.f * s_a11.f;\n\t\ts_a11.f\t = s_v11.f * s_a11.f;\n\t\ts_tmp1.f = s_v21.f * s_tmp2.f;\n\t\ts_a11.f\t = __fadd_rn(s_a11.f, s_tmp1.f);\n\t\ts_tmp1.f = s_v31.f * s_tmp3.f;\n\t\ts_a11.f\t = __fadd_rn(s_a11.f, s_tmp1.f);\n\t\ts_tmp1.f = s_v22.f * s_tmp2.f;\n\t\ts_a12.f\t = __fadd_rn(s_a12.f, s_tmp1.f);\n\t\ts_tmp1.f = s_v32.f * s_tmp3.f;\n\t\ts_a12.f\t = __fadd_rn(s_a12.f, s_tmp1.f);\n\t\ts_tmp1.f = s_v23.f * s_tmp2.f;\n\t\ts_a13.f\t = __fadd_rn(s_a13.f, s_tmp1.f);\n\t\ts_tmp1.f = s_v33.f * s_tmp3.f;\n\t\ts_a13.f\t = __fadd_rn(s_a13.f, s_tmp1.f);\n\n\t\ts_tmp2.f = s_a22.f;\n\t\ts_tmp3.f = s_a23.f;\n\t\ts_a22.f\t = s_v12.f * s_a21.f;\n\t\ts_a23.f\t = s_v13.f * s_a21.f;\n\t\ts_a21.f\t = s_v11.f * s_a21.f;\n\t\ts_tmp1.f = s_v21.f * s_tmp2.f;\n\t\ts_a21.f\t = __fadd_rn(s_a21.f, s_tmp1.f);\n\t\ts_tmp1.f = s_v31.f * s_tmp3.f;\n\t\ts_a21.f\t = __fadd_rn(s_a21.f, s_tmp1.f);\n\t\ts_tmp1.f = s_v22.f * s_tmp2.f;\n\t\ts_a22.f\t = __fadd_rn(s_a22.f, s_tmp1.f);\n\t\ts_tmp1.f = s_v32.f * s_tmp3.f;\n\t\ts_a22.f\t = __fadd_rn(s_a22.f, s_tmp1.f);\n\t\ts_tmp1.f = s_v23.f * s_tmp2.f;\n\t\ts_a23.f\t = __fadd_rn(s_a23.f, s_tmp1.f);\n\t\ts_tmp1.f = s_v33.f * s_tmp3.f;\n\t\ts_a23.f\t = __fadd_rn(s_a23.f, s_tmp1.f);\n\n\t\ts_tmp2.f = s_a32.f;\n\t\ts_tmp3.f = s_a33.f;\n\t\ts_a32.f\t = s_v12.f * s_a31.f;\n\t\ts_a33.f\t = s_v13.f * s_a31.f;\n\t\ts_a31.f\t = s_v11.f * s_a31.f;\n\t\ts_tmp1.f = s_v21.f * s_tmp2.f;\n\t\ts_a31.f\t = __fadd_rn(s_a31.f, s_tmp1.f);\n\t\ts_tmp1.f = s_v31.f * s_tmp3.f;\n\t\ts_a31.f\t = __fadd_rn(s_a31.f, s_tmp1.f);\n\t\ts_tmp1.f = s_v22.f * s_tmp2.f;\n\t\ts_a32.f\t = __fadd_rn(s_a32.f, s_tmp1.f);\n\t\ts_tmp1.f = s_v32.f * s_tmp3.f;\n\t\ts_a32.f\t = __fadd_rn(s_a32.f, s_tmp1.f);\n\t\ts_tmp1.f = s_v23.f * s_tmp2.f;\n\t\ts_a33.f\t = __fadd_rn(s_a33.f, s_tmp1.f);\n\t\ts_tmp1.f = s_v33.f * s_tmp3.f;\n\t\ts_a33.f\t = __fadd_rn(s_a33.f, s_tmp1.f);\n\n\t\t//###########################################################\n\t\t// Permute columns such that the singular values are sorted\n\t\t//###########################################################\n\n\t\ts_tmp1.f = s_a11.f * s_a11.f;\n\t\ts_tmp4.f = s_a21.f * s_a21.f;\n\t\ts_tmp1.f = __fadd_rn(s_tmp1.f, s_tmp4.f);\n\t\ts_tmp4.f = s_a31.f * s_a31.f;\n\t\ts_tmp1.f = __fadd_rn(s_tmp1.f, s_tmp4.f);\n\n\t\ts_tmp2.f = s_a12.f * s_a12.f;\n\t\ts_tmp4.f = s_a22.f * s_a22.f;\n\t\ts_tmp2.f = __fadd_rn(s_tmp2.f, s_tmp4.f);\n\t\ts_tmp4.f = s_a32.f * s_a32.f;\n\t\ts_tmp2.f = __fadd_rn(s_tmp2.f, s_tmp4.f);\n\n\t\ts_tmp3.f = s_a13.f * s_a13.f;\n\t\ts_tmp4.f = s_a23.f * s_a23.f;\n\t\ts_tmp3.f = __fadd_rn(s_tmp3.f, s_tmp4.f);\n\t\ts_tmp4.f = s_a33.f * s_a33.f;\n\t\ts_tmp3.f = __fadd_rn(s_tmp3.f, s_tmp4.f);\n\n\t\t// Swap columns 1-2 if necessary\n\n\t\ts_tmp4.ui = (s_tmp1.f < s_tmp2.f) ? 0xffffffff : 0;\n\t\ts_tmp5.ui = s_a11.ui ^ s_a12.ui;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_a11.ui = s_a11.ui ^ s_tmp5.ui;\n\t\ts_a12.ui = s_a12.ui ^ s_tmp5.ui;\n\n\t\ts_tmp5.ui = s_a21.ui ^ s_a22.ui;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_a21.ui = s_a21.ui ^ s_tmp5.ui;\n\t\ts_a22.ui = s_a22.ui ^ s_tmp5.ui;\n\n\t\ts_tmp5.ui = s_a31.ui ^ s_a32.ui;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_a31.ui = s_a31.ui ^ s_tmp5.ui;\n\t\ts_a32.ui = s_a32.ui ^ s_tmp5.ui;\n\n\t\ts_tmp5.ui = s_v11.ui ^ s_v12.ui;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_v11.ui = s_v11.ui ^ s_tmp5.ui;\n\t\ts_v12.ui = s_v12.ui ^ s_tmp5.ui;\n\n\t\ts_tmp5.ui = s_v21.ui ^ s_v22.ui;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_v21.ui = s_v21.ui ^ s_tmp5.ui;\n\t\ts_v22.ui = s_v22.ui ^ s_tmp5.ui;\n\n\t\ts_tmp5.ui = s_v31.ui ^ s_v32.ui;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_v31.ui = s_v31.ui ^ s_tmp5.ui;\n\t\ts_v32.ui = s_v32.ui ^ s_tmp5.ui;\n\n\t\ts_tmp5.ui = s_tmp1.ui ^ s_tmp2.ui;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_tmp1.ui = s_tmp1.ui ^ s_tmp5.ui;\n\t\ts_tmp2.ui = s_tmp2.ui ^ s_tmp5.ui;\n\n\t\t// If columns 1-2 have been swapped, negate 2nd column of A and V so that V is still a rotation\n\n\t\ts_tmp5.f = -2.f;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_tmp4.f = 1.f;\n\t\ts_tmp4.f = __fadd_rn(s_tmp4.f, s_tmp5.f);\n\n\t\ts_a12.f = s_a12.f * s_tmp4.f;\n\t\ts_a22.f = s_a22.f * s_tmp4.f;\n\t\ts_a32.f = s_a32.f * s_tmp4.f;\n\n\t\ts_v12.f = s_v12.f * s_tmp4.f;\n\t\ts_v22.f = s_v22.f * s_tmp4.f;\n\t\ts_v32.f = s_v32.f * s_tmp4.f;\n\n\t\t// Swap columns 1-3 if necessary\n\n\t\ts_tmp4.ui = (s_tmp1.f < s_tmp3.f) ? 0xffffffff : 0;\n\t\ts_tmp5.ui = s_a11.ui ^ s_a13.ui;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_a11.ui = s_a11.ui ^ s_tmp5.ui;\n\t\ts_a13.ui = s_a13.ui ^ s_tmp5.ui;\n\n\t\ts_tmp5.ui = s_a21.ui ^ s_a23.ui;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_a21.ui = s_a21.ui ^ s_tmp5.ui;\n\t\ts_a23.ui = s_a23.ui ^ s_tmp5.ui;\n\n\t\ts_tmp5.ui = s_a31.ui ^ s_a33.ui;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_a31.ui = s_a31.ui ^ s_tmp5.ui;\n\t\ts_a33.ui = s_a33.ui ^ s_tmp5.ui;\n\n\t\ts_tmp5.ui = s_v11.ui ^ s_v13.ui;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_v11.ui = s_v11.ui ^ s_tmp5.ui;\n\t\ts_v13.ui = s_v13.ui ^ s_tmp5.ui;\n\n\t\ts_tmp5.ui = s_v21.ui ^ s_v23.ui;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_v21.ui = s_v21.ui ^ s_tmp5.ui;\n\t\ts_v23.ui = s_v23.ui ^ s_tmp5.ui;\n\n\t\ts_tmp5.ui = s_v31.ui ^ s_v33.ui;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_v31.ui = s_v31.ui ^ s_tmp5.ui;\n\t\ts_v33.ui = s_v33.ui ^ s_tmp5.ui;\n\n\t\ts_tmp5.ui = s_tmp1.ui ^ s_tmp3.ui;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_tmp1.ui = s_tmp1.ui ^ s_tmp5.ui;\n\t\ts_tmp3.ui = s_tmp3.ui ^ s_tmp5.ui;\n\n\t\t// If columns 1-3 have been swapped, negate 1st column of A and V so that V is still a rotation\n\n\t\ts_tmp5.f = -2.f;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_tmp4.f = 1.f;\n\t\ts_tmp4.f = __fadd_rn(s_tmp4.f, s_tmp5.f);\n\n\t\ts_a11.f = s_a11.f * s_tmp4.f;\n\t\ts_a21.f = s_a21.f * s_tmp4.f;\n\t\ts_a31.f = s_a31.f * s_tmp4.f;\n\n\t\ts_v11.f = s_v11.f * s_tmp4.f;\n\t\ts_v21.f = s_v21.f * s_tmp4.f;\n\t\ts_v31.f = s_v31.f * s_tmp4.f;\n\n\t\t// Swap columns 2-3 if necessary\n\n\t\ts_tmp4.ui = (s_tmp2.f < s_tmp3.f) ? 0xffffffff : 0;\n\t\ts_tmp5.ui = s_a12.ui ^ s_a13.ui;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_a12.ui = s_a12.ui ^ s_tmp5.ui;\n\t\ts_a13.ui = s_a13.ui ^ s_tmp5.ui;\n\n\t\ts_tmp5.ui = s_a22.ui ^ s_a23.ui;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_a22.ui = s_a22.ui ^ s_tmp5.ui;\n\t\ts_a23.ui = s_a23.ui ^ s_tmp5.ui;\n\n\t\ts_tmp5.ui = s_a32.ui ^ s_a33.ui;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_a32.ui = s_a32.ui ^ s_tmp5.ui;\n\t\ts_a33.ui = s_a33.ui ^ s_tmp5.ui;\n\n\t\ts_tmp5.ui = s_v12.ui ^ s_v13.ui;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_v12.ui = s_v12.ui ^ s_tmp5.ui;\n\t\ts_v13.ui = s_v13.ui ^ s_tmp5.ui;\n\n\t\ts_tmp5.ui = s_v22.ui ^ s_v23.ui;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_v22.ui = s_v22.ui ^ s_tmp5.ui;\n\t\ts_v23.ui = s_v23.ui ^ s_tmp5.ui;\n\n\t\ts_tmp5.ui = s_v32.ui ^ s_v33.ui;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_v32.ui = s_v32.ui ^ s_tmp5.ui;\n\t\ts_v33.ui = s_v33.ui ^ s_tmp5.ui;\n\n\t\ts_tmp5.ui = s_tmp2.ui ^ s_tmp3.ui;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_tmp2.ui = s_tmp2.ui ^ s_tmp5.ui;\n\t\ts_tmp3.ui = s_tmp3.ui ^ s_tmp5.ui;\n\n\t\t// If columns 2-3 have been swapped, negate 3rd column of A and V so that V is still a rotation\n\n\t\ts_tmp5.f = -2.f;\n\t\ts_tmp5.ui = s_tmp5.ui & s_tmp4.ui;\n\t\ts_tmp4.f = 1.f;\n\t\ts_tmp4.f = __fadd_rn(s_tmp4.f, s_tmp5.f);\n\n\t\ts_a13.f = s_a13.f * s_tmp4.f;\n\t\ts_a23.f = s_a23.f * s_tmp4.f;\n\t\ts_a33.f = s_a33.f * s_tmp4.f;\n\n\t\ts_v13.f = s_v13.f * s_tmp4.f;\n\t\ts_v23.f = s_v23.f * s_tmp4.f;\n\t\ts_v33.f = s_v33.f * s_tmp4.f;\n\n\t\t//###########################################################\n\t\t// Construct QR factorization of A*V (=U*D) using Givens rotations\n\t\t//###########################################################\n\n\t\ts_u11.f = 1.f;\n\t\ts_u12.f = 0.f;\n\t\ts_u13.f = 0.f;\n\t\ts_u21.f = 0.f;\n\t\ts_u22.f = 1.f;\n\t\ts_u23.f = 0.f;\n\t\ts_u31.f = 0.f;\n\t\ts_u32.f = 0.f;\n\t\ts_u33.f = 1.f;\n\n\t\ts_sh.f\t= s_a21.f * s_a21.f;\n\t\ts_sh.ui = (s_sh.f >= gsmall_number) ? 0xffffffff : 0;\n\t\ts_sh.ui = s_sh.ui & s_a21.ui;\n\n\t\ts_tmp5.f = 0.f;\n\t\ts_ch.f\t = __fsub_rn(s_tmp5.f, s_a11.f);\n\t\ts_ch.f\t = max(s_ch.f, s_a11.f);\n\t\ts_ch.f\t = max(s_ch.f, gsmall_number);\n\t\ts_tmp5.ui = (s_a11.f >= s_tmp5.f) ? 0xffffffff : 0;\n\n\t\ts_tmp1.f = s_ch.f * s_ch.f;\n\t\ts_tmp2.f = s_sh.f * s_sh.f;\n\t\ts_tmp2.f = __fadd_rn(s_tmp1.f, s_tmp2.f);\n\t\ts_tmp1.f = __frsqrt_rn(s_tmp2.f);\n\n\t\ts_tmp4.f = s_tmp1.f * 0.5f;\n\t\ts_tmp3.f = s_tmp1.f * s_tmp4.f;\n\t\ts_tmp3.f = s_tmp1.f * s_tmp3.f;\n\t\ts_tmp3.f = s_tmp2.f * s_tmp3.f;\n\t\ts_tmp1.f = __fadd_rn(s_tmp1.f, s_tmp4.f);\n\t\ts_tmp1.f = __fsub_rn(s_tmp1.f, s_tmp3.f);\n\t\ts_tmp1.f = s_tmp1.f * s_tmp2.f;\n\n\t\ts_ch.f = __fadd_rn(s_ch.f, s_tmp1.f);\n\n\t\ts_tmp1.ui = ~s_tmp5.ui & s_sh.ui;\n\t\ts_tmp2.ui = ~s_tmp5.ui & s_ch.ui;\n\t\ts_ch.ui\t = s_tmp5.ui & s_ch.ui;\n\t\ts_sh.ui\t = s_tmp5.ui & s_sh.ui;\n\t\ts_ch.ui\t = s_ch.ui | s_tmp1.ui;\n\t\ts_sh.ui\t = s_sh.ui | s_tmp2.ui;\n\n\t\ts_tmp1.f = s_ch.f * s_ch.f;\n\t\ts_tmp2.f = s_sh.f * s_sh.f;\n\t\ts_tmp2.f = __fadd_rn(s_tmp1.f, s_tmp2.f);\n\t\ts_tmp1.f = __frsqrt_rn(s_tmp2.f);\n\n\t\ts_tmp4.f = s_tmp1.f * 0.5f;\n\t\ts_tmp3.f = s_tmp1.f * s_tmp4.f;\n\t\ts_tmp3.f = s_tmp1.f * s_tmp3.f;\n\t\ts_tmp3.f = s_tmp2.f * s_tmp3.f;\n\t\ts_tmp1.f = __fadd_rn(s_tmp1.f, s_tmp4.f);\n\t\ts_tmp1.f = __fsub_rn(s_tmp1.f, s_tmp3.f);\n\n\t\ts_ch.f = s_ch.f * s_tmp1.f;\n\t\ts_sh.f = s_sh.f * s_tmp1.f;\n\n\t\ts_c.f = s_ch.f * s_ch.f;\n\t\ts_s.f = s_sh.f * s_sh.f;\n\t\ts_c.f = __fsub_rn(s_c.f, s_s.f);\n\t\ts_s.f = s_sh.f * s_ch.f;\n\t\ts_s.f = __fadd_rn(s_s.f, s_s.f);\n\n\t\t//###########################################################\n\t\t// Rotate matrix A\n\t\t//###########################################################\n\n\t\ts_tmp1.f = s_s.f * s_a11.f;\n\t\ts_tmp2.f = s_s.f * s_a21.f;\n\t\ts_a11.f\t = s_c.f * s_a11.f;\n\t\ts_a21.f\t = s_c.f * s_a21.f;\n\t\ts_a11.f\t = __fadd_rn(s_a11.f, s_tmp2.f);\n\t\ts_a21.f\t = __fsub_rn(s_a21.f, s_tmp1.f);\n\n\t\ts_tmp1.f = s_s.f * s_a12.f;\n\t\ts_tmp2.f = s_s.f * s_a22.f;\n\t\ts_a12.f\t = s_c.f * s_a12.f;\n\t\ts_a22.f\t = s_c.f * s_a22.f;\n\t\ts_a12.f\t = __fadd_rn(s_a12.f, s_tmp2.f);\n\t\ts_a22.f\t = __fsub_rn(s_a22.f, s_tmp1.f);\n\n\t\ts_tmp1.f = s_s.f * s_a13.f;\n\t\ts_tmp2.f = s_s.f * s_a23.f;\n\t\ts_a13.f\t = s_c.f * s_a13.f;\n\t\ts_a23.f\t = s_c.f * s_a23.f;\n\t\ts_a13.f\t = __fadd_rn(s_a13.f, s_tmp2.f);\n\t\ts_a23.f\t = __fsub_rn(s_a23.f, s_tmp1.f);\n\n\t\t//###########################################################\n\t\t// Update matrix U\n\t\t//###########################################################\n\n\t\ts_tmp1.f = s_s.f * s_u11.f;\n\t\ts_tmp2.f = s_s.f * s_u12.f;\n\t\ts_u11.f\t = s_c.f * s_u11.f;\n\t\ts_u12.f\t = s_c.f * s_u12.f;\n\t\ts_u11.f\t = __fadd_rn(s_u11.f, s_tmp2.f);\n\t\ts_u12.f\t = __fsub_rn(s_u12.f, s_tmp1.f);\n\n\t\ts_tmp1.f = s_s.f * s_u21.f;\n\t\ts_tmp2.f = s_s.f * s_u22.f;\n\t\ts_u21.f\t = s_c.f * s_u21.f;\n\t\ts_u22.f\t = s_c.f * s_u22.f;\n\t\ts_u21.f\t = __fadd_rn(s_u21.f, s_tmp2.f);\n\t\ts_u22.f\t = __fsub_rn(s_u22.f, s_tmp1.f);\n\n\t\ts_tmp1.f = s_s.f * s_u31.f;\n\t\ts_tmp2.f = s_s.f * s_u32.f;\n\t\ts_u31.f\t = s_c.f * s_u31.f;\n\t\ts_u32.f\t = s_c.f * s_u32.f;\n\t\ts_u31.f\t = __fadd_rn(s_u31.f, s_tmp2.f);\n\t\ts_u32.f\t = __fsub_rn(s_u32.f, s_tmp1.f);\n\n\t\t// Second Givens rotation\n\n\t\ts_sh.f\t= s_a31.f * s_a31.f;\n\t\ts_sh.ui = (s_sh.f >= gsmall_number) ? 0xffffffff : 0;\n\t\ts_sh.ui = s_sh.ui & s_a31.ui;\n\n\t\ts_tmp5.f = 0.f;\n\t\ts_ch.f\t = __fsub_rn(s_tmp5.f, s_a11.f);\n\t\ts_ch.f\t = max(s_ch.f, s_a11.f);\n\t\ts_ch.f\t = max(s_ch.f, gsmall_number);\n\t\ts_tmp5.ui = (s_a11.f >= s_tmp5.f) ? 0xffffffff : 0;\n\n\t\ts_tmp1.f = s_ch.f * s_ch.f;\n\t\ts_tmp2.f = s_sh.f * s_sh.f;\n\t\ts_tmp2.f = __fadd_rn(s_tmp1.f, s_tmp2.f);\n\t\ts_tmp1.f = __frsqrt_rn(s_tmp2.f);\n\n\t\ts_tmp4.f = s_tmp1.f * 0.5;\n\t\ts_tmp3.f = s_tmp1.f * s_tmp4.f;\n\t\ts_tmp3.f = s_tmp1.f * s_tmp3.f;\n\t\ts_tmp3.f = s_tmp2.f * s_tmp3.f;\n\t\ts_tmp1.f = __fadd_rn(s_tmp1.f, s_tmp4.f);\n\t\ts_tmp1.f = __fsub_rn(s_tmp1.f, s_tmp3.f);\n\t\ts_tmp1.f = s_tmp1.f * s_tmp2.f;\n\n\t\ts_ch.f = __fadd_rn(s_ch.f, s_tmp1.f);\n\n\t\ts_tmp1.ui = ~s_tmp5.ui & s_sh.ui;\n\t\ts_tmp2.ui = ~s_tmp5.ui & s_ch.ui;\n\t\ts_ch.ui\t = s_tmp5.ui & s_ch.ui;\n\t\ts_sh.ui\t = s_tmp5.ui & s_sh.ui;\n\t\ts_ch.ui\t = s_ch.ui | s_tmp1.ui;\n\t\ts_sh.ui\t = s_sh.ui | s_tmp2.ui;\n\n\t\ts_tmp1.f = s_ch.f * s_ch.f;\n\t\ts_tmp2.f = s_sh.f * s_sh.f;\n\t\ts_tmp2.f = __fadd_rn(s_tmp1.f, s_tmp2.f);\n\t\ts_tmp1.f = __frsqrt_rn(s_tmp2.f);\n\n\t\ts_tmp4.f = s_tmp1.f * 0.5f;\n\t\ts_tmp3.f = s_tmp1.f * s_tmp4.f;\n\t\ts_tmp3.f = s_tmp1.f * s_tmp3.f;\n\t\ts_tmp3.f = s_tmp2.f * s_tmp3.f;\n\t\ts_tmp1.f = __fadd_rn(s_tmp1.f, s_tmp4.f);\n\t\ts_tmp1.f = __fsub_rn(s_tmp1.f, s_tmp3.f);\n\n\t\ts_ch.f = s_ch.f * s_tmp1.f;\n\t\ts_sh.f = s_sh.f * s_tmp1.f;\n\n\t\ts_c.f = s_ch.f * s_ch.f;\n\t\ts_s.f = s_sh.f * s_sh.f;\n\t\ts_c.f = __fsub_rn(s_c.f, s_s.f);\n\t\ts_s.f = s_sh.f * s_ch.f;\n\t\ts_s.f = __fadd_rn(s_s.f, s_s.f);\n\n\t\t//###########################################################\n\t\t// Rotate matrix A\n\t\t//###########################################################\n\n\t\ts_tmp1.f = s_s.f * s_a11.f;\n\t\ts_tmp2.f = s_s.f * s_a31.f;\n\t\ts_a11.f\t = s_c.f * s_a11.f;\n\t\ts_a31.f\t = s_c.f * s_a31.f;\n\t\ts_a11.f\t = __fadd_rn(s_a11.f, s_tmp2.f);\n\t\ts_a31.f\t = __fsub_rn(s_a31.f, s_tmp1.f);\n\n\t\ts_tmp1.f = s_s.f * s_a12.f;\n\t\ts_tmp2.f = s_s.f * s_a32.f;\n\t\ts_a12.f\t = s_c.f * s_a12.f;\n\t\ts_a32.f\t = s_c.f * s_a32.f;\n\t\ts_a12.f\t = __fadd_rn(s_a12.f, s_tmp2.f);\n\t\ts_a32.f\t = __fsub_rn(s_a32.f, s_tmp1.f);\n\n\t\ts_tmp1.f = s_s.f * s_a13.f;\n\t\ts_tmp2.f = s_s.f * s_a33.f;\n\t\ts_a13.f\t = s_c.f * s_a13.f;\n\t\ts_a33.f\t = s_c.f * s_a33.f;\n\t\ts_a13.f\t = __fadd_rn(s_a13.f, s_tmp2.f);\n\t\ts_a33.f\t = __fsub_rn(s_a33.f, s_tmp1.f);\n\n\t\t//###########################################################\n\t\t// Update matrix U\n\t\t//###########################################################\n\n\t\ts_tmp1.f = s_s.f * s_u11.f;\n\t\ts_tmp2.f = s_s.f * s_u13.f;\n\t\ts_u11.f\t = s_c.f * s_u11.f;\n\t\ts_u13.f\t = s_c.f * s_u13.f;\n\t\ts_u11.f\t = __fadd_rn(s_u11.f, s_tmp2.f);\n\t\ts_u13.f\t = __fsub_rn(s_u13.f, s_tmp1.f);\n\n\t\ts_tmp1.f = s_s.f * s_u21.f;\n\t\ts_tmp2.f = s_s.f * s_u23.f;\n\t\ts_u21.f\t = s_c.f * s_u21.f;\n\t\ts_u23.f\t = s_c.f * s_u23.f;\n\t\ts_u21.f\t = __fadd_rn(s_u21.f, s_tmp2.f);\n\t\ts_u23.f\t = __fsub_rn(s_u23.f, s_tmp1.f);\n\n\t\ts_tmp1.f = s_s.f * s_u31.f;\n\t\ts_tmp2.f = s_s.f * s_u33.f;\n\t\ts_u31.f\t = s_c.f * s_u31.f;\n\t\ts_u33.f\t = s_c.f * s_u33.f;\n\t\ts_u31.f\t = __fadd_rn(s_u31.f, s_tmp2.f);\n\t\ts_u33.f\t = __fsub_rn(s_u33.f, s_tmp1.f);\n\n\t\t// Third Givens Rotation\n\n\t\ts_sh.f\t= s_a32.f * s_a32.f;\n\t\ts_sh.ui = (s_sh.f >= gsmall_number) ? 0xffffffff : 0;\n\t\ts_sh.ui = s_sh.ui & s_a32.ui;\n\n\t\ts_tmp5.f = 0.f;\n\t\ts_ch.f\t = __fsub_rn(s_tmp5.f, s_a22.f);\n\t\ts_ch.f\t = max(s_ch.f, s_a22.f);\n\t\ts_ch.f\t = max(s_ch.f, gsmall_number);\n\t\ts_tmp5.ui = (s_a22.f >= s_tmp5.f) ? 0xffffffff : 0;\n\n\t\ts_tmp1.f = s_ch.f * s_ch.f;\n\t\ts_tmp2.f = s_sh.f * s_sh.f;\n\t\ts_tmp2.f = __fadd_rn(s_tmp1.f, s_tmp2.f);\n\t\ts_tmp1.f = __frsqrt_rn(s_tmp2.f);\n\n\t\ts_tmp4.f = s_tmp1.f * 0.5f;\n\t\ts_tmp3.f = s_tmp1.f * s_tmp4.f;\n\t\ts_tmp3.f = s_tmp1.f * s_tmp3.f;\n\t\ts_tmp3.f = s_tmp2.f * s_tmp3.f;\n\t\ts_tmp1.f = __fadd_rn(s_tmp1.f, s_tmp4.f);\n\t\ts_tmp1.f = __fsub_rn(s_tmp1.f, s_tmp3.f);\n\t\ts_tmp1.f = s_tmp1.f * s_tmp2.f;\n\n\t\ts_ch.f = __fadd_rn(s_ch.f, s_tmp1.f);\n\n\t\ts_tmp1.ui = ~s_tmp5.ui & s_sh.ui;\n\t\ts_tmp2.ui = ~s_tmp5.ui & s_ch.ui;\n\t\ts_ch.ui\t = s_tmp5.ui & s_ch.ui;\n\t\ts_sh.ui\t = s_tmp5.ui & s_sh.ui;\n\t\ts_ch.ui\t = s_ch.ui | s_tmp1.ui;\n\t\ts_sh.ui\t = s_sh.ui | s_tmp2.ui;\n\n\t\ts_tmp1.f = s_ch.f * s_ch.f;\n\t\ts_tmp2.f = s_sh.f * s_sh.f;\n\t\ts_tmp2.f = __fadd_rn(s_tmp1.f, s_tmp2.f);\n\t\ts_tmp1.f = __frsqrt_rn(s_tmp2.f);\n\n\t\ts_tmp4.f = s_tmp1.f * 0.5f;\n\t\ts_tmp3.f = s_tmp1.f * s_tmp4.f;\n\t\ts_tmp3.f = s_tmp1.f * s_tmp3.f;\n\t\ts_tmp3.f = s_tmp2.f * s_tmp3.f;\n\t\ts_tmp1.f = __fadd_rn(s_tmp1.f, s_tmp4.f);\n\t\ts_tmp1.f = __fsub_rn(s_tmp1.f, s_tmp3.f);\n\n\t\ts_ch.f = s_ch.f * s_tmp1.f;\n\t\ts_sh.f = s_sh.f * s_tmp1.f;\n\n\t\ts_c.f = s_ch.f * s_ch.f;\n\t\ts_s.f = s_sh.f * s_sh.f;\n\t\ts_c.f = __fsub_rn(s_c.f, s_s.f);\n\t\ts_s.f = s_sh.f * s_ch.f;\n\t\ts_s.f = __fadd_rn(s_s.f, s_s.f);\n\n\t\t//###########################################################\n\t\t// Rotate matrix A\n\t\t//###########################################################\n\n\t\ts_tmp1.f = s_s.f * s_a21.f;\n\t\ts_tmp2.f = s_s.f * s_a31.f;\n\t\ts_a21.f\t = s_c.f * s_a21.f;\n\t\ts_a31.f\t = s_c.f * s_a31.f;\n\t\ts_a21.f\t = __fadd_rn(s_a21.f, s_tmp2.f);\n\t\ts_a31.f\t = __fsub_rn(s_a31.f, s_tmp1.f);\n\n\t\ts_tmp1.f = s_s.f * s_a22.f;\n\t\ts_tmp2.f = s_s.f * s_a32.f;\n\t\ts_a22.f\t = s_c.f * s_a22.f;\n\t\ts_a32.f\t = s_c.f * s_a32.f;\n\t\ts_a22.f\t = __fadd_rn(s_a22.f, s_tmp2.f);\n\t\ts_a32.f\t = __fsub_rn(s_a32.f, s_tmp1.f);\n\n\t\ts_tmp1.f = s_s.f * s_a23.f;\n\t\ts_tmp2.f = s_s.f * s_a33.f;\n\t\ts_a23.f\t = s_c.f * s_a23.f;\n\t\ts_a33.f\t = s_c.f * s_a33.f;\n\t\ts_a23.f\t = __fadd_rn(s_a23.f, s_tmp2.f);\n\t\ts_a33.f\t = __fsub_rn(s_a33.f, s_tmp1.f);\n\n\t\t//###########################################################\n\t\t// Update matrix U\n\t\t//###########################################################\n\n\t\ts_tmp1.f = s_s.f * s_u12.f;\n\t\ts_tmp2.f = s_s.f * s_u13.f;\n\t\ts_u12.f\t = s_c.f * s_u12.f;\n\t\ts_u13.f\t = s_c.f * s_u13.f;\n\t\ts_u12.f\t = __fadd_rn(s_u12.f, s_tmp2.f);\n\t\ts_u13.f\t = __fsub_rn(s_u13.f, s_tmp1.f);\n\n\t\ts_tmp1.f = s_s.f * s_u22.f;\n\t\ts_tmp2.f = s_s.f * s_u23.f;\n\t\ts_u22.f\t = s_c.f * s_u22.f;\n\t\ts_u23.f\t = s_c.f * s_u23.f;\n\t\ts_u22.f\t = __fadd_rn(s_u22.f, s_tmp2.f);\n\t\ts_u23.f\t = __fsub_rn(s_u23.f, s_tmp1.f);\n\n\t\ts_tmp1.f = s_s.f * s_u32.f;\n\t\ts_tmp2.f = s_s.f * s_u33.f;\n\t\ts_u32.f\t = s_c.f * s_u32.f;\n\t\ts_u33.f\t = s_c.f * s_u33.f;\n\t\ts_u32.f\t = __fadd_rn(s_u32.f, s_tmp2.f);\n\t\ts_u33.f\t = __fsub_rn(s_u33.f, s_tmp1.f);\n\n\t\tv11 = s_v11.f;\n\t\tv12 = s_v12.f;\n\t\tv13 = s_v13.f;\n\t\tv21 = s_v21.f;\n\t\tv22 = s_v22.f;\n\t\tv23 = s_v23.f;\n\t\tv31 = s_v31.f;\n\t\tv32 = s_v32.f;\n\t\tv33 = s_v33.f;\n\n\t\tu11 = s_u11.f;\n\t\tu12 = s_u12.f;\n\t\tu13 = s_u13.f;\n\t\tu21 = s_u21.f;\n\t\tu22 = s_u22.f;\n\t\tu23 = s_u23.f;\n\t\tu31 = s_u31.f;\n\t\tu32 = s_u32.f;\n\t\tu33 = s_u33.f;\n\n\t\ts11 = s_a11.f;\n\t\t//s12 = s_a12.f; s13 = s_a13.f; s21 = s_a21.f;\n\t\ts22 = s_a22.f;\n\t\t//s23 = s_a23.f; s31 = s_a31.f; s32 = s_a32.f;\n\t\ts33 = s_a33.f;\n\t}\n\n\t/**\n \\brief 2x2 SVD (singular value decomposition) A=USV'\n \\param[in] A Input matrix.\n \\param[out] u Robustly a rotation matrix in Givens form\n \\param[out] sigma Vector of singular values sorted with decreasing magnitude. The second one can be negative.\n \\param[out] V Robustly a rotation matrix in Givens form\n*/\n\ttemplate\n\t__forceinline__ __host__ __device__ void singular_value_decomposition(const std::array& aa, GivensRotation& u, std::array& sigma, GivensRotation& v) {\n\t\tstd::array s_sym;///< column-major\n\t\tstd::array a {aa[0], aa[1], aa[2], aa[3]};\n\t\tpolar_decomposition(a, u, s_sym);\n\t\tdouble cosine;\n\t\tdouble sine;\n\t\tdouble x = s_sym[0];\n\t\tdouble y = s_sym[2];\n\t\tdouble z = s_sym[3];\n\t\tdouble y2 = y * y;\n\t\tif(y2 == 0) {\n\t\t\t// S is already diagonal\n\t\t\tcosine\t = 1;\n\t\t\tsine\t = 0;\n\t\t\tsigma[0] = x;\n\t\t\tsigma[1] = z;\n\t\t} else {\n\t\t\tdouble tau = T(0.5) * (x - z);\n\t\t\tdouble w = sqrt(tau * tau + y2);\n\t\t\t// w > y > 0\n\t\t\tdouble t;\n\t\t\tif(tau > 0) {\n\t\t\t\t// tau + w > w > y > 0 ==> division is safe\n\t\t\t\tt = y / (tau + w);\n\t\t\t} else {\n\t\t\t\t// tau - w < -w < -y < 0 ==> division is safe\n\t\t\t\tt = y / (tau - w);\n\t\t\t}\n\t\t\tcosine = T(1) / sqrt(t * t + T(1));\n\t\t\tsine = -t * cosine;\n\t\t\t/*\n v = [cosine -sine; sine cosine]\n sigma = v'SV. Only compute the diagonals for efficiency.\n Also utilize symmetry of S and don't form v yet.\n */\n\t\t\tdouble c2 = cosine * cosine;\n\t\t\tdouble csy = 2 * cosine * sine * y;\n\t\t\tdouble s2 = sine * sine;\n\t\t\tsigma[0] = c2 * x - csy + s2 * z;\n\t\t\tsigma[1] = s2 * x + csy + c2 * z;\n\t\t}\n\n\t\t// Sorting\n\t\t// Polar already guarantees negative sign is on the small magnitude singular value.\n\t\tif(sigma[0] < sigma[1]) {\n\t\t\tstd::swap(sigma[0], sigma[1]);\n\t\t\tv.c = -sine;\n\t\t\tv.s = cosine;\n\t\t} else {\n\t\t\tv.c = cosine;\n\t\t\tv.s = sine;\n\t\t}\n\t\tu *= v;\n\t}\n\n\ttemplate\n\t__forceinline__ __device__ void svd(const std::array& f, std::array& u, std::array& s, std::array& v) {\n\t\tprintf(\"Not implemented yet!\\n\");\n\t}\n\n\t/**\n \\brief 2x2 SVD (singular value decomposition) a=USV'\n \\param[in] a Input matrix.\n \\param[out] u Robustly a rotation matrix.\n \\param[out] sigma Vector of singular values sorted with decreasing magnitude. The second one can be negative.\n \\param[out] v Robustly a rotation matrix.\n*/\n\ttemplate<>\n\t__forceinline__ __device__ void svd(const std::array& a, std::array& u, std::array& sigma, std::array& v) {\n\t\tGivensRotation gv(0, 1);\n\t\tGivensRotation gu(0, 1);\n\t\tsingular_value_decomposition(a, gu, sigma, gv);\n\n\t\tgu.template fill<2, float>(u);\n\t\tgv.template fill<2, float>(v);\n\t}\n\n\ttemplate<>\n\t__forceinline__ __device__ void svd(const std::array& a, std::array& u, std::array& sigma, std::array& v) {\n\t\tGivensRotation gv(0, 1);\n\t\tGivensRotation gu(0, 1);\n\t\tsingular_value_decomposition(a, gu, sigma, gv);\n\n\t\tgu.template fill<2, double>(u);\n\t\tgv.template fill<2, double>(v);\n\t}\n\n\ttemplate<>\n\t__forceinline__ __device__ void svd(const std::array& f, std::array& u, std::array& s, std::array& v) {\n\t\tsvd(f[0], f[3], f[6], f[1], f[4], f[7], f[2], f[5], f[8], u[0], u[3], u[6], u[1], u[4], u[7], u[2], u[5], u[8], s[0], s[1], s[2], v[0], v[3], v[6], v[1], v[4], v[7], v[2], v[5], v[8]);\n\t}\n\n\ttemplate<>\n\t__forceinline__ __device__ void svd(const std::array& f, std::array& u, std::array& s, std::array& v) {\n\t\tsvd(f[0], f[3], f[6], f[1], f[4], f[7], f[2], f[5], f[8], u[0], u[3], u[6], u[1], u[4], u[7], u[2], u[5], u[8], s[0], s[1], s[2], v[0], v[3], v[6], v[1], v[4], v[7], v[2], v[5], v[8]);\n\t}\n\n}// namespace math\n\n}// namespace mn\n\n#endif\n" }, { "path": "Library/MnBase/Math/Probability/Probability.cpp", "content": "#include \"Probability.h\"\n\n#ifdef _WIN32\n#\tifndef M_PI\n#\t\tdefine M_PI 3.14159265358979323846//NOLINT(cppcoreguidelines-macro-usage) M_PI is usually a macro\n#\tendif\n#endif\n\nnamespace mn {\nPropability::Propability()\n\t: distribution(0.0, 1.0)\n\t, generator(device()) {}\n\ndouble Propability::pdf(double lambda, int k) {\n\tdouble pdf_value = 1;\n\tint i;\n\tfor(i = 1; i <= k; ++i) {\n\t\tpdf_value *= lambda / static_cast(i);\n\t}\n\treturn pdf_value * exp(-1.0 * lambda);\n}\n\ndouble Propability::pdf(double u, double o, double x) {\n\tstatic const double CO = 1.0 / sqrt(2 * M_PI);\t\t\t //NOLINT(readability-magic-numbers) Formula specific\n\tdouble index\t\t = -(x - u) * (x - u) / 2.0 / o / o;//NOLINT(readability-magic-numbers) Formula specific\n\treturn CO / o * exp(index);\n}\n\ndouble Propability::anti_normal_pdf(double u, double o, double x) {\n\tstatic const double CO = 1.0 / sqrt(2 * M_PI);\t\t\t //NOLINT(readability-magic-numbers) Formula specific\n\tdouble index\t\t = -(x - u) * (x - u) / 2.0 / o / o;//NOLINT(readability-magic-numbers) Formula specific\n\treturn 1 - CO / o * exp(index);\n}\n\nint Propability::rand_p(double lambda) {\n\tdouble u = distribution(generator);\n\tint x\t = 0;\n\tdouble cdf = exp(-1.0 * lambda);\n\twhile(u >= cdf) {\n\t\tx++;\n\t\tcdf += pdf(lambda, x);\n\t}\n\treturn x;\n}\n\nint Propability::rand_normal(double u, double o) {\n\tdouble val = distribution(generator);\n\tint x\t = 0;\n\tdouble cdf = 0;// pdf(u, o, x)\n\twhile(val >= cdf) {\n\t\tx++;\n\t\tcdf += pdf(u, o, static_cast(x));\n\t}\n\treturn x;\n}\n\nint Propability::rand_anti_normal(double u, double o) {\n\tdouble val = distribution(generator);\n\tint x\t = 0;\n\tdouble cdf = 0;// pdf(u, o, x)\n\twhile(val >= cdf) {\n\t\tx++;\n\t\tcdf += anti_normal_pdf(u, o, static_cast(x));\n\t}\n\treturn x;\n}\n}// namespace mn" }, { "path": "Library/MnBase/Math/Probability/Probability.h", "content": "#ifndef PROBABILITY_H\n#define PROBABILITY_H\n\n#include \n#include \n\nnamespace mn {\n\nclass Propability {\n\tstd::uniform_real_distribution distribution;\n\tstd::random_device device;\n\tstd::mt19937 generator;\n\n\tPropability();\n\n public:\n\tstatic double pdf(double lambda, int k);\n\tint rand_p(double lambda);\n\tstatic double anti_normal_pdf(double u, double o, double x);\n\n\tstatic double pdf(double u, double o, double x);\n\tint rand_normal(double u, double o);\n\tint rand_anti_normal(double u, double o);\n};\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Math/Vec.h", "content": "#ifndef MN_VEC_H\n#define MN_VEC_H\n#include \n#include \n#include \n#include \n\n#include \"MnBase/Meta/MathMeta.h\"\n#include \"MnBase/Meta/Meta.h\"\n#include \"MnBase/Meta/PatternMeta.h\"\n#include \"MnBase/Meta/Relationship.h\"\n\n#define ENABLE_BITWISE_OPERATORS 0\n\nnamespace mn {\n\nstruct identity_vec {};\n\n/// declarations\ntemplate\nstruct indexer_impl;\n\ntemplate\nstruct vec_view;\n\ntemplate\nstruct vec_impl;\n\ntemplate\nusing indexer = indexer_impl>;\n\ntemplate\nusing vec = vec_impl>;\n\n/// indexer\ntemplate\nstruct indexer_impl> {\n\tstatic constexpr auto dim\t = sizeof...(Ns);\n\tstatic constexpr auto extent = integral_seq_mul::value;\n\n\tusing index_type = Tn;\n\tusing extends\t = std::integer_sequence;\n\n\ttemplate\n\t__host__ __device__ static constexpr Tn range(std::integral_constant i) {\n\t\t(void) i;\n\t\treturn select_value::value;// select_indexed_value::value;\n\t}\n\n\ttemplate\n\t__host__ __device__ static constexpr Tn offset_impl(std::index_sequence seq, Args&&... args) {\n\t\t(void) seq;\n\n\t\tTn idx = 0;\n\t\t(void) std::initializer_list {(idx += std::forward(args) * excl_suffix_mul {}, 0)...};\n\t\treturn idx;\n\t}\n\n\ttemplate = 0>\n\t__host__ __device__ static constexpr Tn offset(Args&&... args) {\n\t\treturn offset_impl(std::index_sequence_for {}, std::forward(args)...);\n\t}\n};\n\n/// vec without lifetime managing\ntemplate\nstruct vec_view>\n\t: identity_vec\n\t, indexer {\n private:\n\tT* m_data;\n\n public:\n\tusing base_t = indexer;\n\tusing base_t::dim;\n\tusing base_t::extent;\n\tusing value_type = T;\n\tusing base_t::offset;\n\tusing typename base_t::extends;\n\tusing typename base_t::index_type;\n\n\tconstexpr vec_view() = delete;\n\t__host__ __device__ explicit constexpr vec_view(T* ptr)\n\t\t: m_data {ptr} {}\n\n\t/// random access\n\t// ()\n\ttemplate = 0>\n\t__host__ __device__ constexpr T& operator()(Args&&... args) noexcept {\n\t\treturn m_data[offset(std::forward(args)...)];\n\t}\n\ttemplate = 0>\n\t__host__ __device__ constexpr const T& operator()(Args&&... args) const noexcept {\n\t\treturn m_data[offset(std::forward(args)...)];\n\t}\n\n\t// []\n\ttemplate, 1>, extends>>, Tn D = dim, enable_if_t<(D > 1)> = 0>\n\t__host__ __device__ constexpr R operator[](Index&& index) noexcept {\n\t\treturn R {m_data + offset(std::forward(index))};\n\t}\n\ttemplate, gather_t, 1>, extends>>, Tn D = dim, enable_if_t<(D > 1)> = 0>\n\t__host__ __device__ constexpr R operator[](Index index) const noexcept {\n\t\treturn R {m_data + offset(std::forward(index))};\n\t}\n\ttemplate = 0>\n\t__host__ __device__ constexpr T& operator[](Index index) noexcept {\n\t\treturn m_data[std::forward(index)];\n\t}\n\ttemplate = 0>\n\t__host__ __device__ constexpr const T& operator[](Index index) const noexcept {\n\t\treturn m_data[std::forward(index)];\n\t}\n\n\ttemplate\n\t__host__ __device__ constexpr T& val(Index index) noexcept {\n\t\treturn m_data[std::forward(index)];\n\t}\n\ttemplate\n\t__host__ __device__ constexpr const T& val(Index index) const noexcept {\n\t\treturn m_data[std::forward(index)];\n\t}\n};\n\n/// vec\ntemplate\nstruct vec_impl>\n\t: identity_vec\n\t, indexer {\n\tstatic_assert(std::is_trivial::value, \"Vec element type is not trivial!\\n\");\n\n\tusing base_t = indexer;\n\tusing base_t::dim;\n\tusing base_t::extent;\n\tusing value_type = T;\n\tusing base_t::offset;\n\tusing typename base_t::extends;\n\tusing typename base_t::index_type;\n\n private:\n\tstd::array m_data;\n\n public:\n\t/// construct\n\tconstexpr vec_impl() = default;\n\n\ttemplate::value...> = 0>\n\t__host__ __device__ explicit constexpr vec_impl(Vals&&... vals) noexcept\n\t\t: m_data {std::forward(vals)...} {}\n\n\ttemplate 1), std::is_convertible::value> = 0>\n\t__host__ __device__ explicit constexpr vec_impl(Val&& val) noexcept {\n\t\tfor(Tn idx = 0; idx < extent; ++idx) {\n\t\t\tm_data[idx] = std::forward(val);\n\t\t}\n\t}\n\n\t__host__ __device__ constexpr void set(T val) noexcept {\n\t\tfor(Tn idx = 0; idx < extent; ++idx) {\n\t\t\tm_data[idx] = val;\n\t\t}\n\t}\n\n\t/// expose internal\n\t__host__ __device__ constexpr auto data() noexcept -> T* {\n\t\treturn m_data.data();\n\t}\n\t__host__ __device__ constexpr auto data() const noexcept -> const T* {\n\t\treturn m_data.data();\n\t}\n\t__host__ __device__ constexpr std::array& data_arr() noexcept {\n\t\treturn m_data;\n\t}\n\t__host__ __device__ constexpr const std::array& data_arr() const noexcept {\n\t\treturn m_data;\n\t}\n\n\t/// random access\n\t// ()\n\ttemplate = 0>\n\t__host__ __device__ constexpr T& operator()(Args&&... args) noexcept {\n\t\treturn m_data[offset(std::forward(args)...)];\n\t}\n\ttemplate = 0>\n\t__host__ __device__ constexpr const T& operator()(Args&&... args) const noexcept {\n\t\treturn m_data[offset(std::forward(args)...)];\n\t}\n\n\t// []\n\ttemplate, 1>, extends>>, Tn D = dim, enable_if_t<(D > 1)> = 0>\n\t__host__ __device__ constexpr R operator[](Index&& index) noexcept {\n\t\treturn R {m_data.data() + offset(std::forward(index))};\n\t}\n\ttemplate, gather_t, 1>, extends>>, Tn D = dim, enable_if_t<(D > 1)> = 0>\n\t__host__ __device__ constexpr R operator[](Index index) const noexcept {\n\t\treturn R {m_data.data() + offset(std::forward(index))};\n\t}\n\ttemplate = 0>\n\t__host__ __device__ constexpr T& operator[](Index index) noexcept {\n\t\treturn m_data[std::forward(index)];\n\t}\n\ttemplate = 0>\n\t__host__ __device__ constexpr const T& operator[](Index index) const noexcept {\n\t\treturn m_data[std::forward(index)];\n\t}\n\n\ttemplate\n\t__host__ __device__ constexpr T& val(Index index) noexcept {\n\t\treturn m_data[std::forward(index)];\n\t}\n\ttemplate\n\t__host__ __device__ constexpr const T& val(Index index) const noexcept {\n\t\treturn m_data[std::forward(index)];\n\t}\n\t///\n\n\ttemplate\n\t__host__ __device__ constexpr auto cast() const noexcept {\n\t\tvec_impl r {};\n\t\tfor(Tn idx = 0; idx < extent; ++idx) {\n\t\t\tr.val(idx) = m_data[idx];\n\t\t}\n\t\treturn r;\n\t}\n\n\t/// compare\n\ttemplate::value, is_same::value, std::is_convertible::value> = 0>\n\t__host__ __device__ constexpr auto operator==(Vec&& o) noexcept -> bool {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tif(m_data[i] != std::forward(o).val(i)) {\n\t\t\t\treturn false;\n\t\t\t}\n\t\t}\n\t\treturn true;\n\t}\n\ttemplate::value, is_same::value, std::is_convertible::value> = 0>\n\t__host__ __device__ constexpr auto operator!=(Vec&& o) noexcept -> bool {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tif(m_data[i] == std::forward(o).val(i)) {\n\t\t\t\treturn false;\n\t\t\t}\n\t\t}\n\t\treturn true;\n\t}\n\n\t/// linalg\n\ttemplate>\n\t__host__ __device__ constexpr R dot(vec_impl const& o) const noexcept {\n\t\tR res {0};\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tres += m_data[i] * o.val(i);\n\t\t}\n\t\treturn res;\n\t}\n\ttemplate>\n\t__host__ __device__ constexpr R dot(vec_impl&& o) const noexcept {\n\t\tR res {0};\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tres += m_data[i] * o.val(i);\n\t\t}\n\t\treturn res;\n\t}\n\t__host__ __device__ constexpr T prod() noexcept {\n\t\tT res {1};\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tres *= m_data[i];\n\t\t}\n\t\treturn res;\n\t}\n\t__host__ __device__ constexpr T l2NormSqr() noexcept {\n\t\tT res {0};\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tres += m_data[i] * m_data[i];\n\t\t}\n\t\treturn res;\n\t}\n\t__host__ __device__ constexpr T infNormSqr() noexcept {\n\t\tT res {0};\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tT sqr = m_data[i] * m_data[i];\n\t\t\tif(sqr > res) {\n\t\t\t\tres = sqr;\n\t\t\t}\n\t\t}\n\t\treturn res;\n\t}\n\n\t/// borrowed from\n\t/// https://github.com/cemyuksel/cyCodeBase/blob/master/cyIVector.h\n\t/// east const\n\t//!@name Unary operators\n\t__host__ __device__ constexpr vec_impl operator-() const noexcept {\n\t\tvec_impl r;\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = -m_data[i];\n\t\t}\n\t\treturn r;\n\t}\n\n\t//!@name Binary operators\n\t// scalar\n\ttemplate>\n\t__host__ __device__ friend constexpr auto operator+(vec_impl const& e, TT const v) noexcept {\n\t\tvec_impl r {};\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = e.val(i) + v;\n\t\t}\n\t\treturn r;\n\t}\n\ttemplate>\n\t__host__ __device__ friend constexpr auto operator+(TT const v, vec_impl const& e) noexcept {\n\t\tvec_impl r {};\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = e.val(i) + v;\n\t\t}\n\t\treturn r;\n\t}\n\ttemplate>\n\t__host__ __device__ friend constexpr auto operator-(vec_impl const& e, TT const v) noexcept {\n\t\tvec_impl r {};\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = e.val(i) - v;\n\t\t}\n\t\treturn r;\n\t}\n\ttemplate>\n\t__host__ __device__ friend constexpr auto operator-(TT const v, vec_impl const& e) noexcept {\n\t\tvec_impl r {};\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = v - e.val(i);\n\t\t}\n\t\treturn r;\n\t}\n\ttemplate>\n\t__host__ __device__ friend constexpr auto operator*(vec_impl const& e, TT const v) noexcept {\n\t\tvec_impl r {};\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = e.val(i) * v;\n\t\t}\n\t\treturn r;\n\t}\n\ttemplate>\n\t__host__ __device__ friend constexpr auto operator*(TT const v, vec_impl const& e) noexcept {\n\t\tvec_impl r {};\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = e.val(i) * v;\n\t\t}\n\t\treturn r;\n\t}\n\ttemplate>\n\t__host__ __device__ friend constexpr auto operator/(vec_impl const& e, TT const v) noexcept {\n\t\tvec_impl r {};\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = e.val(i) / v;\n\t\t}\n\t\treturn r;\n\t}\n\ttemplate>\n\t__host__ __device__ friend constexpr auto operator/(TT const v, vec_impl const& e) noexcept {\n\t\tvec_impl r {};\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = v / e.val(i);\n\t\t}\n\t\treturn r;\n\t}\n\t// vector\n\ttemplate>\n\t__host__ __device__ constexpr auto operator+(vec_impl const& o) const noexcept {\n\t\tvec_impl r {};\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = m_data[i] + o.val(i);\n\t\t}\n\t\treturn r;\n\t}\n\ttemplate>\n\t__host__ __device__ constexpr auto operator+(vec_impl&& o) const noexcept {\n\t\tvec_impl r {};\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = m_data[i] + o.val(i);\n\t\t}\n\t\treturn r;\n\t}\n\ttemplate>\n\t__host__ __device__ constexpr auto operator-(vec_impl const& o) const noexcept {\n\t\tvec_impl r {};\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = m_data[i] - o.val(i);\n\t\t}\n\t\treturn r;\n\t}\n\ttemplate>\n\t__host__ __device__ constexpr auto operator-(vec_impl&& o) const noexcept {\n\t\tvec_impl r {};\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = m_data[i] - o.val(i);\n\t\t}\n\t\treturn r;\n\t}\n\ttemplate>\n\t__host__ __device__ constexpr auto operator*(vec_impl const& o) const noexcept {\n\t\tvec_impl r {};\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = m_data[i] * o.val(i);\n\t\t}\n\t\treturn r;\n\t}\n\ttemplate>\n\t__host__ __device__ constexpr auto operator*(vec_impl&& o) const noexcept {\n\t\tvec_impl r {};\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = m_data[i] * o.val(i);\n\t\t}\n\t\treturn r;\n\t}\n\ttemplate>\n\t__host__ __device__ constexpr auto operator/(vec_impl const& o) const noexcept {\n\t\tvec_impl r {};\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = m_data[i] / o.val(i);\n\t\t}\n\t\treturn r;\n\t}\n\ttemplate>\n\t__host__ __device__ constexpr auto operator/(vec_impl&& o) const noexcept {\n\t\tvec_impl r {};\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = m_data[i] / o.val(i);\n\t\t}\n\t\treturn r;\n\t}\n\t//!@name Assignment operators\n\t// scalar\n\ttemplate::value> = 0>\n\t__host__ __device__ constexpr vec_impl& operator+=(TT&& v) noexcept {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tm_data[i] += std::forward(v);\n\t\t}\n\t\treturn *this;\n\t}\n\ttemplate::value> = 0>\n\t__host__ __device__ constexpr vec_impl& operator-=(TT&& v) noexcept {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tm_data[i] -= std::forward(v);\n\t\t}\n\t\treturn *this;\n\t}\n\ttemplate::value> = 0>\n\t__host__ __device__ constexpr vec_impl& operator*=(TT&& v) noexcept {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tm_data[i] *= std::forward(v);\n\t\t}\n\t\treturn *this;\n\t}\n\ttemplate::value> = 0>\n\t__host__ __device__ constexpr vec_impl& operator/=(TT&& v) noexcept {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tm_data[i] /= std::forward(v);\n\t\t}\n\t\treturn *this;\n\t}\n\n\t// vector\n\ttemplate::value> = 0>\n\t__host__ __device__ constexpr vec_impl& operator+=(vec_impl const& o) noexcept {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tm_data[i] += o.val(i);\n\t\t}\n\t\treturn *this;\n\t}\n\ttemplate::value> = 0>\n\t__host__ __device__ constexpr vec_impl& operator+=(vec_impl&& o) noexcept {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tm_data[i] += o.val(i);\n\t\t}\n\t\treturn *this;\n\t}\n\ttemplate::value> = 0>\n\t__host__ __device__ constexpr vec_impl& operator-=(vec_impl const& o) noexcept {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tm_data[i] -= o.val(i);\n\t\t}\n\t\treturn *this;\n\t}\n\ttemplate::value> = 0>\n\t__host__ __device__ constexpr vec_impl& operator-=(vec_impl&& o) noexcept {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tm_data[i] -= o.val(i);\n\t\t}\n\t\treturn *this;\n\t}\n\ttemplate::value> = 0>\n\t__host__ __device__ constexpr vec_impl& operator*=(vec_impl const& o) noexcept {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tm_data[i] *= o.val(i);\n\t\t}\n\t\treturn *this;\n\t}\n\ttemplate::value> = 0>\n\t__host__ __device__ constexpr vec_impl& operator*=(vec_impl&& o) noexcept {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tm_data[i] *= o.val(i);\n\t\t}\n\t\treturn *this;\n\t}\n\ttemplate::value> = 0>\n\t__host__ __device__ constexpr vec_impl& operator/=(vec_impl const& o) noexcept {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tm_data[i] /= o.val(i);\n\t\t}\n\t\treturn *this;\n\t}\n\ttemplate::value> = 0>\n\t__host__ __device__ constexpr vec_impl& operator/=(vec_impl&& o) noexcept {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tm_data[i] /= o.val(i);\n\t\t}\n\t\treturn *this;\n\t}\n\n#if ENABLE_BITWISE_OPERATORS\n\t//!@name Bitwise operators\n\t__host__ __device__ vec_impl operator<<(vec_impl const& o) const noexcept {\n\t\tvec_impl r;\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = m_data[i] << o.val(i);\n\t\t}\n\t\treturn r;\n\t}\n\t__host__ __device__ vec_impl operator>>(vec_impl const& o) const noexcept {\n\t\tvec_impl r;\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = m_data[i] >> o.val(i);\n\t\t}\n\t\treturn r;\n\t}\n\t__host__ __device__ vec_impl operator&(vec_impl const& o) const noexcept {\n\t\tvec_impl r;\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = m_data[i] & o.val(i);\n\t\t}\n\t\treturn r;\n\t}\n\t__host__ __device__ vec_impl operator|(vec_impl const& o) const noexcept {\n\t\tvec_impl r;\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = m_data[i] | o.val(i);\n\t\t}\n\t\treturn r;\n\t}\n\t__host__ __device__ vec_impl operator^(vec_impl const& o) const noexcept {\n\t\tvec_impl r;\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = m_data[i] ^ o.val(i);\n\t\t}\n\t\treturn r;\n\t}\n\t__host__ __device__ vec_impl operator<<(T const v) const noexcept {\n\t\tvec_impl r;\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = m_data[i] << v;\n\t\t}\n\t\treturn r;\n\t}\n\t__host__ __device__ vec_impl operator>>(T const v) const noexcept {\n\t\tvec_impl r;\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = m_data[i] >> v;\n\t\t}\n\t\treturn r;\n\t}\n\t__host__ __device__ vec_impl operator&(T const v) const noexcept {\n\t\tvec_impl r;\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = m_data[i] & v;\n\t\t}\n\t\treturn r;\n\t}\n\t__host__ __device__ vec_impl operator|(T const v) const noexcept {\n\t\tvec_impl r;\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = m_data[i] | v;\n\t\t}\n\t\treturn r;\n\t}\n\t__host__ __device__ vec_impl operator^(T const v) const noexcept {\n\t\tvec_impl r;\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tr.val(i) = m_data[i] ^ v;\n\t\t}\n\t\treturn r;\n\t}\n\n\t//!@name Bitwise Assignment operators\n\t__host__ __device__ vec_impl& operator<<=(vec_impl const& o) noexcept {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tm_data[i] <<= o.val(i);\n\t\t}\n\t\treturn *this;\n\t}\n\t__host__ __device__ vec_impl& operator>>=(vec_impl const& o) noexcept {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tm_data[i] >>= o.val(i);\n\t\t}\n\t\treturn *this;\n\t}\n\t__host__ __device__ vec_impl& operator&=(vec_impl const& o) noexcept {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tm_data[i] &= o.val(i);\n\t\t}\n\t\treturn *this;\n\t}\n\t__host__ __device__ vec_impl& operator|=(vec_impl const& o) noexcept {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tm_data[i] |= o.val(i);\n\t\t}\n\t\treturn *this;\n\t}\n\t__host__ __device__ vec_impl& operator^=(vec_impl const& o) noexcept {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tm_data[i] ^= o.val(i);\n\t\t}\n\t\treturn *this;\n\t}\n\t__host__ __device__ vec_impl& operator<<=(T const v) noexcept {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tm_data[i] <<= v;\n\t\t}\n\t\treturn *this;\n\t}\n\t__host__ __device__ vec_impl& operator>>=(T const v) noexcept {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tm_data[i] >>= v;\n\t\t}\n\t\treturn *this;\n\t}\n\t__host__ __device__ vec_impl& operator&=(T const v) noexcept {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tm_data[i] &= v;\n\t\t}\n\t\treturn *this;\n\t}\n\t__host__ __device__ vec_impl& operator|=(T const v) noexcept {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tm_data[i] |= v;\n\t\t}\n\t\treturn *this;\n\t}\n\t__host__ __device__ vec_impl& operator^=(T const v) noexcept {\n\t\tfor(int i = 0; i < extent; ++i) {\n\t\t\tm_data[i] ^= v;\n\t\t}\n\t\treturn *this;\n\t}\n#endif\n};\n\n/// affine map = linear map + translation matrix+(0, 0, 1) point(vec+{1})\n/// vector(vec+{0}) homogeneous coordinates\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Memory/Allocator.h", "content": "#ifndef ALLOCATOR_H\n#define ALLOCATOR_H\n\n#include \n\n#include \"MemoryResource.h\"\n\nnamespace mn {\n\n/// stateless allocator\nstruct HeapAllocator {\n\tusing mr_type = MemoryResource;\n\n\tHeapAllocator() = default;\n\tHeapAllocator(const HeapAllocator& o) noexcept {}\n\n\tmr_type* resource() const {\n\t\treturn &HeapMemoryResource::instance();\n\t}\n\n\tvoid* allocate(std::size_t bytes) {\n\t\treturn resource()->allocate(bytes);\n\t}\n\tvoid deallocate(void* p, std::size_t bytes) {\n\t\t(void) bytes;\n\n\t\tresource()->deallocate(p);\n\t}\n};\n\n/// stateful allocator\ntemplate\nstruct StackAllocator {\n\tusing mr_type = MemoryResource;\n\n private:\n\tmr_type* mr;\n\n public:\n\tchar* data;\n\tchar* head;\n\tchar* tail;\n\tstd::size_t align;\n\n\tStackAllocator() = delete;\n\texplicit StackAllocator(mr_type* mr, std::size_t align_bytes, std::size_t total_mem_bytes)\n\t\t: mr {mr}\n\t\t, align {align_bytes} {\n\t\tdata = head = (char*) (mr->allocate(total_mem_bytes));\n\t\ttail\t\t= head + total_mem_bytes;\n\t};\n\n\t~StackAllocator() {\n\t\tmr->deallocate((void*) data, (std::size_t)(tail - data));\n\t}\n\n\tmr_type* resource() const noexcept {\n\t\treturn mr;\n\t}\n\n\t/// learnt from taichi\n\tvoid* allocate(std::size_t bytes) {\n\t\t/// first align head\n\t\tchar* ret = head + align - 1 - ((std::size_t) head + align - 1) % align;\n\t\thead\t = ret + bytes;\n\t\tif(head > tail) {\n\t\t\tthrow std::bad_alloc {};\n\t\t} else {\n\t\t\treturn ret;\n\t\t}\n\t}\n\tvoid deallocate(void* p, std::size_t bytes) {\n\t\t(void) bytes;\n\n\t\tif(p >= head) {\n\t\t\tthrow std::bad_alloc {};\n\t\t} else if(p < data) {\n\t\t\tthrow std::bad_alloc {};\n\t\t}\n\t\thead = (char*) p;\n\t}\n\n\tvoid reset() {\n\t\thead = data;\n\t}\n};\n\ntemplate\nstruct ObjectAllocator {\n\tusing value_type = value_t;\n\tusing mr_type\t = MemoryResource;\n\n private:\n\tmr_type* mr;\n\n public:\n\tObjectAllocator() = delete;\n\tObjectAllocator(mr_type* mr)\n\t\t: mr {mr} {};\n\n\ttemplate\n\texplicit ObjectAllocator(const ObjectAllocator& o) noexcept {\n\t\tmr = o.resource();\n\t}\n\n\tmr_type* resource() const noexcept {\n\t\treturn mr;\n\t}\n\n\tvalue_type* allocate(std::size_t n) {\n\t\treturn (value_type*) (mr->allocate(n * sizeof(value_type), alignof(value_type)));\n\t}\n\n\tvoid deallocate(value_type* p, std::size_t n) {\n\t\tmr->deallocate((void*) p, n * sizeof(value_type), alignof(value_type));\n\t}\n};\n\ntemplate\nstruct PoolAllocator {\n\tstatic constexpr std::size_t chunk_size = chunk_size_v;\n\n\tusing mr_type = MemoryResource;\n};\n\ntemplate\nusing page_allocator = PoolAllocator<4096, MemoryResource_t>;\n\ntemplate\nstruct structural_allocator : PoolAllocator {};\n\n/// 4K, 64K, 2M\ntemplate\nstruct multiPoolAllocator;\n\ntemplate\nstruct multiPoolAllocator, MemoryResource_t> : PoolAllocator... {};\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Memory/MemObj.h", "content": "#ifndef MEM_OBJ_H\n#define MEM_OBJ_H\n\nnamespace mn {\n\nstruct MemBackend {\n\tusing uchar = unsigned char;\n\n\tenum class Physical : uchar {\n\t\tCPU = 0,\n\t\tGPU = 1\n\t};\n};\n\nstruct MemResource {\n\tunion {\n\t\tvoid* ptr;\n\t\tuintptr_t ptrval;\n\t\tuint64_t offset;///< only legal for 64-bit app\n\t};\n};\n\nstruct MemStack {\n\tchar* top;\n\tchar* end;\n};\n\nstruct MemBlock {\n\tvoid* mem;\n\tstd::size_t size;\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Memory/MemoryResource.h", "content": "#ifndef MEMORY_RESOURCE_H\n#define MEMORY_RESOURCE_H\n#include \"MnBase/Singleton.h\"\n\nnamespace mn {\n\ntemplate\nstruct MemoryResource {\n\tusing pointer_t = void*;\n\n\tpointer_t allocate(std::size_t bytes, std::size_t alignment = alignof(max_align_t)) {\n\t\treturn static_cast(*this).do_allocate(bytes, alignment);\n\t}\n\n\tvoid deallocate(pointer_t ptr, std::size_t bytes = 0, std::size_t alignment = alignof(max_align_t)) {\n\t\tstatic_cast(*this).do_deallocate(ptr, bytes, alignment);\n\t}\n\n\tbool is_equal(const MemoryResource& other) const noexcept {\n\t\treturn (this == &other);\n\t}\n};\n\nstruct HeapMemoryResource\n\t: Singleton\n\t, MemoryResource {\n\tvoid* do_allocate(std::size_t bytes, std::size_t align) {\n\t\t// return ::operator new(bytes, std::align_val_t(align));\n\t\treturn ::operator new(bytes);\n\t}\n\n\tvoid do_deallocate(void* ptr, std::size_t bytes, std::size_t align) {\n\t\t//::operator delete(ptr, bytes, std::align_val_t(align));\n\t\t::operator delete(ptr);\n\t}\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Meta/AllocMeta.cuh", "content": "#ifndef ALLOC_META_H\n#define ALLOC_META_H\n\n#include \n#include \n\n#include \"MnSystem/Cuda/HostUtils.hpp\"\n#include \"TypeMeta.h\"\n\nnamespace mn {\n\n/** HEAP **/\n\ntemplate\nauto make_vector(Args&&... args) {\n\tusing Item = std::common_type_t;\n\tstd::vector result(sizeof...(Args));\n\t// works as a building block\n\tforArgs(\n\t\t[&result](auto&& x) {\n\t\t\tresult.emplace_back(std::forward(x));\n\t\t},\n\t\tstd::forward(args)...\n\t);\n\treturn result;\n}\n\n/** CUDA **/\n\ntemplate\nauto cuda_alloc(Integer size) -> Type* {\n\tType* addr {nullptr};\n\tcheckCudaErrors(cudaMalloc(static_cast(static_cast(&addr)), sizeof(Type) * size));\n\treturn addr;\n}\n\ntemplate\nauto cuda_virtual_alloc(Integer size) -> Type* {\n\tType* addr {nullptr};\n\tcheckCudaErrors(cudaMallocManaged(static_cast(static_cast(&addr)), sizeof(Type) * size));\n\treturn addr;\n}\n\ntemplate\nauto cuda_alloc(Integer size, AllocFunc&& allocFunc) -> Type* {\n\treturn static_cast(static_cast((std::forward(allocFunc)(sizeof(Type) * size))));\n}\n\n#if 0\ntemplate auto cuda_allocs(Integer size) {\n std::array>::value> addrs;\n forIndexAlloc(\n [&addrs, size](std::size_t &&i, std::size_t &&typeSize) {\n checkCudaErrors(cudaMalloc(&addrs[i], typeSize * size));\n },\n std::make_index_sequence>::value>{});\n return std::move(addrs);\n}\n\ntemplate \nauto cuda_virtual_allocs(Integer size) {\n std::array>::value> addrs;\n forIndexAlloc(\n [&addrs, size](std::size_t &&i, std::size_t &&typeSize) {\n checkCudaErrors(cudaMallocManaged(&addrs[i], typeSize * size));\n },\n std::make_index_sequence>::value>{});\n return std::move(addrs);\n}\n\ntemplate \nauto cuda_allocs(const Integer *sizes) {\n std::array>::value> addrs;\n forIndexAlloc(\n [&addrs, &sizes](std::size_t &&i, std::size_t &&typeSize) {\n checkCudaErrors(cudaMalloc(&addrs[i], typeSize * sizes[i]));\n },\n std::make_index_sequence>::value>{});\n return std::move(addrs);\n}\n\ntemplate \nauto cuda_virtual_allocs(const Integer *sizes) {\n std::array>::value> addrs;\n forIndexAlloc(\n [&addrs, &sizes](std::size_t &&i, std::size_t &&typeSize) {\n checkCudaErrors(cudaMallocManaged(&addrs[i], typeSize * sizes[i]));\n },\n std::make_index_sequence>::value>{});\n return std::move(addrs);\n}\n\ntemplate \nauto cuda_allocs(Integer size, AllocFunc &&allocFunc) {\n std::array>::value> addrs;\n forIndexAlloc(\n [&addrs, &allocFunc, size](std::size_t &&i, std::size_t &&typeSize) {\n addrs[i] = std::forward(allocFunc)(typeSize * size);\n },\n std::make_index_sequence>::value>{});\n return std::move(addrs);\n}\n\ntemplate void cuda_frees(std::array &_attribs) {\n for (auto &attrib : _attribs){\n checkCudaErrors(cudaFree(attrib));\n }\n}\n\ntemplate void cuda_free(Type *addr) {\n checkCudaErrors(cudaFree(addr));\n}\n\ntemplate \nvoid cuda_memcpys(const Integer size, Attribs &&from, Attribs &&to,\n cudaStream_t stream = cudaStreamDefault) {\n forIndexAlloc(\n [&from, &to, &size, &stream](std::size_t &&i, std::size_t &&typeSize) {\n cudaMemcpyAsync(to[i], from[i], typeSize * size,\n cudaMemcpyDeviceToDevice, stream);\n },\n std::make_index_sequence>::value>{});\n}\n#endif\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Meta/ControlFlow.h", "content": "#ifndef CONTROL_FLOW_H\n#define CONTROL_FLOW_H\n#include \n\n#include \"Meta.h\"\n\nnamespace mn {\n\n// enable_if\n// conditional\ntemplate\nstruct conditional_impl {\n\ttemplate\n\tusing type = T;\n};\ntemplate<>\nstruct conditional_impl {\n\ttemplate\n\tusing type = F;\n};\n\ntemplate\nusing conditional_t = typename conditional_impl::type;\n\ntemplate\nstruct do_if;\ntemplate<>\nstruct do_if {\n\ttemplate\n\tauto operator()(F&& f, Args&&... args) {\n\t\treturn std::forward(f)(std::forward(args)...);\n\t}\n};\ntemplate<>\nstruct do_if {\n\ttemplate\n\tauto operator()(F&& f, Args&&... args) {}\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Meta/Functional.h", "content": "#ifndef FUNCTIONAL_H\n#define FUNCTIONAL_H\n\n#include \n#include \n\n#include \"Meta.h\"\n#include \"TupleMeta.h\"\n\nnamespace mn {\n\ntemplate\nconstexpr decltype(auto) fold(F&& f, T&& v) {\n\treturn std::forward(v);\n}\n\ntemplate\nconstexpr decltype(auto) fold(F&& f, T&& v, Ts&&... vs) {\n\treturn std::forward(f)(std::forward(v), fold(std::forward(f), std::forward(vs)...));\n}\n\n/// map, transform\n\n/// result_of\n\ntemplate\nstruct add_optionality_t {\n\tusing type = std::optional;\n};\n\ntemplate\nstruct add_optionality_t> {\n\tusing type = std::optional;\n};\n\ntemplate\nusing add_optionality = typename add_optionality_t::type;\n\ntemplate\nauto operator|(std::optional const& opt, Func const& func) -> add_optionality {\n\tif(opt) {\n\t\treturn func(*opt);\n\t} else {\n\t\treturn {};\n\t}\n}\n\ntemplate>::value, int> = 0>\nauto operator|(T&& t, F&& f) -> decltype(detail::void_or_nullopt(t).operator*()))>()) {\n\tusing return_type = decltype(f(std::forward(t).operator*()));\n\tif(t) {\n\t\treturn f(std::forward(t).operator*());\n\t} else {\n\t\treturn detail::void_or_nullopt();\n\t}\n}\n\n}// namespace mn\n\n#endif\n" }, { "path": "Library/MnBase/Meta/MathMeta.h", "content": "#ifndef MATH_META_H\n#define MATH_META_H\n\n#include \n#include \n\n#include \"Meta.h\"\n#include \"MnBase/Math/Bit/Bits.h\"\n#include \"TypeMeta.h\"\n\nnamespace mn {\n\ntemplate\nstruct next_2pow {\n\tstatic_assert(std::is_integral::value, \"next_2pow: template parameter not an integral!\\n\");\n\tstatic constexpr T value = static_cast(1) << bit_count(I);\n};\n\ntemplate\nstruct mul;\ntemplate\nstruct mul : std::integral_constant {};\ntemplate\nstruct mul : std::integral_constant::value> {};\n\ntemplate\nstruct add;\ntemplate\nstruct add : std::integral_constant {};\ntemplate\nstruct add : std::integral_constant::value> {};\n\n/// use some designs from https://github.com/taocpp/sequences/\nnamespace meta_impl {\n\ttemplate\n\tconstexpr T integral_seq_mul_impl() noexcept {\n\t\tT res {1};\n\t\t(void) std::initializer_list {(res *= Ns, 0)...};\n\t\treturn res;\n\t}\n\n\ttemplate\n\tconstexpr T integral_seq_sum_impl() noexcept {\n\t\tT res {0};\n\t\t(void) std::initializer_list {(res += Ns, 0)...};\n\t\treturn res;\n\t}\n}// namespace meta_impl\n\ntemplate\nstruct value_seq_traits_impl;\ntemplate\nstruct value_seq_traits_impl> {\n\tstatic constexpr T sum\t= meta_impl::integral_seq_sum_impl();\n\tstatic constexpr T prod = meta_impl::integral_seq_mul_impl();\n};\ntemplate\nusing value_seq_traits = value_seq_traits_impl>;\n\n/// seq reduction\ntemplate\nusing integral_seq_sum = std::integral_constant 0) ? Ns : 0)...>::sum - value_seq_traits::sum>;\ntemplate\nusing integral_seq_mul = std::integral_constant::prod>;\n\ntemplate\nstruct integral_seq_max;\ntemplate\nstruct integral_seq_max : std::integral_constant {};\ntemplate\nstruct integral_seq_max : std::integral_constant integral_seq_max::value) ? N : integral_seq_max::value> {};\n\n/// prefix sum\ntemplate>\nstruct excl_prefix_sum;\ntemplate>\nstruct incl_prefix_sum;\n\ntemplate\nstruct excl_prefix_sum, std::index_sequence> : integral_seq_sum {\n\tstatic_assert(I < sizeof...(Ns), \"excl_prefix_sum out-of-bound access \");\n\tusing type = integral_seq_sum;\n};\ntemplate\nstruct incl_prefix_sum, std::index_sequence> : integral_seq_sum {\n\tstatic_assert(I < sizeof...(Ns), \"incl_prefix_sum out-of-bound access \");\n\tusing type = integral_seq_sum;\n};\n/// suffix mul\ntemplate>\nstruct excl_suffix_mul;\n\ntemplate\nstruct excl_suffix_mul, std::index_sequence> : integral_seq_mul I ? Ns : 1)...> {\n\tstatic_assert(I < sizeof...(Ns), \"excl_suffix_mul out-of-bound access \");\n\tusing type = integral_seq_mul I ? Ns : 1)...>;\n};\n\n/// seq scan(sum)\ntemplate>\nstruct excl_scan_seq;\ntemplate\nstruct excl_scan_seq> : std::integer_sequence::value...> {\n\tusing type = std::integer_sequence::value...>;\n};\ntemplate\nusing excl_scan_seq_t = typename excl_scan_seq::type;\ntemplate>\nstruct incl_scan_seq;\ntemplate\nstruct incl_scan_seq> : std::integer_sequence::value...> {\n\tusing type = std::integer_sequence::value...>;\n};\ntemplate\nusing incl_scan_seq_t = typename incl_scan_seq::type;\n\n/// seq coefficient-wise arithmetic\ntemplate>\nstruct minus_seq;\ntemplate\nstruct minus_seq> {\n\tstatic_assert(Seq0::size() == Seq1::size(), \"minus_seq error\");\n\tusing type = std::integer_sequence, (select_value::value - select_value::value)...>;\n};\ntemplate\nusing minus_seq_t = typename minus_seq::type;\n\ntemplate\nstruct translate_seq;\ntemplate\nstruct translate_seq, Offset> {\n\tusing type = std::integer_sequence;\n};\ntemplate\nusing translate_seq_t = typename translate_seq::type;\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Meta/Meta.h", "content": "#ifndef META_H\n#define META_H\n\n#include \n#include \n\nnamespace mn {\n\n/// initializer list & function overload\n/// or\nconstexpr bool logic_or(std::initializer_list) {\n\treturn false;\n}\nconstexpr bool logic_or(std::initializer_list) {\n\treturn true;\n}\n/// and\nconstexpr bool logic_and(std::initializer_list) {\n\treturn true;\n}\nconstexpr bool logic_and(std::initializer_list) {\n\treturn false;\n}\n\ntemplate class Predicate, typename... Ts>\nconstexpr bool all_satisfy() {\n\treturn logic_and({typename Predicate::type()...});\n}\ntemplate class Predicate, typename... Ts>\nconstexpr bool any_satisfy() {\n\treturn logic_or({typename Predicate::type()...});\n}\n\n/// pre C++14 impl, https://zh.cppreference.com/w/cpp/types/void_t\n/// check ill-formed types\ntemplate\nstruct make_void {\n\tusing type = void;\n};\ntemplate\nusing void_t = typename make_void::type;\n\n/// SFINAE\ntemplate\nstruct enable_if;\ntemplate<>\nstruct enable_if {\n\tusing type = char;\n};\ntemplate\nusing enable_if_t = typename enable_if::type;\ntemplate\nusing enable_if_all = typename enable_if...>::value>::type;\ntemplate\nusing enable_if_any = typename enable_if()...})>::type;\n/// underlying_type\n/// common_type\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Meta/Optional.h", "content": "#ifndef OPTIONAL_H\n#define OPTIONAL_H\n//#include \n#include \n\nnamespace mn {\n\n// template using optional = mapbox::util::optional;\ntemplate\nusing optional = tl::optional;\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Meta/PatternMeta.h", "content": "#ifndef PATTERN_META_H\n#define PATTERN_META_H\n\n#include \n#include \n\n#include \"TypeMeta.h\"\n\nnamespace mn {\n\ntemplate\nstruct gather;\n\n/// Seq must be integer_sequence\ntemplate\nstruct gather, ValueSeq> {\n\tusing type = std::integer_sequence::value...>;\n};\ntemplate\nusing gather_t = typename gather::type;\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Meta/Polymorphism.h", "content": "#ifndef POLYMORPHISM_H\n#define POLYMORPHISM_H\n//#include \n#include \n\n#define ADVANCED_OVERLOAD_SET 0\n\nnamespace mn {\n\n#if ADVANCED_OVERLOAD_SET\n/// only in c++17\ntemplate\nstruct overload_set : TFs... {\n\tusing TFs::operator()...;\n};\ntemplate\noverload(TFs...)->overload_set;\n#else\n\ntemplate\nstruct overload_set\n\t: TF\n\t, overload_set {\n\tusing TF::operator();\n\tusing overload_set::operator();\n\ttemplate\n\toverload_set(TFFwd&& f, TFsFwd&&... fs)\n\t\t: TF {std::forward(f)}\n\t\t, overload_set {std::forward(fs)...} {}\n};\ntemplate\nstruct overload_set : TF {\n\tusing TF::operator();\n\ttemplate\n\toverload_set(TFFwd&& f)\n\t\t: TF {std::forward(f)} {}\n};\n\ntemplate\nconstexpr auto overload(TFs&&... fs) {\n\treturn overload_set...>(std::forward(fs)...);\n}\n\ntemplate\n//using variant = mapbox::util::variant;\nusing variant = mpark::variant;\n\ntemplate\nauto& get(TVariant&& variant) {\n\t//return mapbox::util::get(std::forward(variant));\n\treturn mpark::get(std::forward(variant));\n}\n\ntemplate\nconstexpr auto match(TVariants&&... vs) {\n\treturn [&vs...](auto&&... fs) -> decltype(auto) {\n\t\tauto visitor = overload(std::forward(fs)...);\n\t\t//return mapbox::util::apply_visitor(visitor, std::forward(vs)...);\n\t\treturn mpark::visit(visitor, std::forward(vs)...);\n\t};\n}\n#endif\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Meta/Relationship.h", "content": "#ifndef RELATIONSHIP_H\n#define RELATIONSHIP_H\n\n#include \"Meta.h\"\n\nnamespace mn {\n\nstruct wrapper_base {\n\tstatic constexpr bool is_same(void*) {\n\t\treturn false;\n\t};\n};\n\ntemplate\nstruct wrapper : wrapper_base {\n\tusing wrapper_base::is_same;\n\tstatic constexpr bool is_same(wrapper*) {\n\t\treturn true;\n\t};\n};\n\ntemplate\nusing is_same = std::integral_constant::is_same((wrapper*) nullptr)>;\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Meta/TupleMeta.h", "content": "#ifndef TUPLE_META_H\n#define TUPLE_META_H\n\n#include \n#include \n#include \n#include \n\n#include \"MathMeta.h\"\n#include \"Meta.h\"\n#include \"PatternMeta.h\"\n#include \"TypeMeta.h\"\n\nnamespace mn {\n\n/// Jorg Brown, Cppcon2019, reducing template compilation overhead using\n/// features from C++11, 14, 17, and 20\nstruct identity_tuple {};\ntemplate\nstruct tuple_value {\n\tstatic constexpr std::size_t tuple_size = 1;\n\n\tT value;\n\n\tconstexpr tuple_value() = default;\n\n\ttemplate\n\texplicit constexpr tuple_value(Args&&... args)\n\t\t: value {std::forward(args)...} {}\n\n\t// constexpr auto &get(std::integral_constant) noexcept {\n\tconstexpr T& get() noexcept {\n\t\treturn value;\n\t}\n\tconstexpr const T& get() const noexcept {\n\t\treturn value;\n\t}\n};\n\ntemplate\nstruct tuple_base;\n\ntemplate\nstruct tuple_base, Ts...> : tuple_value... {\n\tstatic constexpr std::size_t tuple_size = sizeof...(Ts);\n\n\tusing tuple_types = type_seq;\n\n\t// explicit constexpr tuple_base(Ts &&... args) : tuple_leaf(args)...\n\t// {}\n\tconstexpr tuple_base() = default;\n\ttemplate\n\texplicit constexpr tuple_base(Args&&... args)\n\t\t: tuple_value(std::forward(args))... {}\n\n\t/// function overload, disabled due to c++17 feature using expansion\n\t// using tuple_leaf::get...;\n\t// template auto &get() {\n\t// return get(std::integral_constant{});\n\t//}\n\t/// c++14 impl\n\ttemplate\n\tconstexpr auto& get_element(tuple_value* leaf) noexcept {\n\t\treturn *leaf;\n\t}\n\ttemplate\n\tconstexpr typename tuple_types::type& get() noexcept {\n\t\treturn get_element(this).value;\n\t}\n\ttemplate\n\tconstexpr const typename tuple_types::type& get() const noexcept {\n\t\treturn get_element(this).value;\n\t}\n};\n\ntemplate\nstruct tuple_impl;\ntemplate\nstruct tuple_impl> : identity_tuple {\n\tstatic constexpr std::size_t tuple_size = sizeof...(Ts);\n\n\tusing base_t\t = tuple_base, Ts...>;\n\tusing tuple_types = type_seq;\n\n\tbase_t base;\n\n\tconstexpr tuple_impl() = default;\n\ttemplate\n\texplicit constexpr tuple_impl(Args&&... args)\n\t\t: base {std::forward(args)...} {}\n\n\ttemplate\n\tconstexpr auto& get() noexcept {\n\t\treturn base.template get();\n\t}\n\ttemplate\n\tconstexpr const auto& get() const noexcept {\n\t\treturn base.template get();\n\t}\n};\ntemplate\nusing tuple = tuple_impl>;\n\ntemplate\nusing is_tuple = std::is_base_of;\n\ntemplate\nusing tuple_size = std::integral_constant;\n\ntemplate\nusing tuple_element = select_type;\n\n/// get (ridiculous syntax)\ntemplate\nconstexpr const auto& get(const tuple_impl& t) noexcept {\n\treturn t.template get();\n\t// return static_cast>\n\t// &>(t.base).get();\n}\ntemplate\nconstexpr typename TypeSeq::type& get(tuple_impl& t) noexcept {\n\treturn t.template get();\n\t// return static_cast>\n\t// &>(t.base).get();\n}\ntemplate\nconstexpr typename TypeSeq::type&& get(tuple_impl&& t) noexcept {\n\treturn std::move(t).template get();\n\t// return static_cast>\n\t// &&>(std::move(t.base)).get();\n}\n\n/// make_tuple\ntemplate...>>\nconstexpr R make_tuple(Args&&... args) {\n\treturn R {std::forward(args)...};\n}\n/// forward as tuple\ntemplate>\nconstexpr R tuple_forward(Ts&&... ts) noexcept {\n\treturn R {std::forward(ts)...};\n}\n\n/// taocpp\nnamespace meta_impl {\n\n\ttemplate\n\tstruct count_less_or_equal;\n\ttemplate\n\tstruct count_less_or_equal> : integral_seq_sum {};\n\n\ttemplate\n\tstruct expand;\n\ttemplate\n\tusing expand_t = typename expand::type;\n\ttemplate\n\tstruct expand, Seq> : std::index_sequence::value...> {\n\t\tusing type = std::index_sequence::value...>;\n\t};\n\n\ttemplate\n\tstruct tuple_cat_result;\n\n\ttemplate\n\tstruct tuple_cat_result, std::index_sequence, Ts...> {\n\t\tusing type = tuple::tuple_types::type...>;\n\t};\n\ttemplate\n\tusing tuple_cat_result_t = typename tuple_cat_result::type;\n\n\ttemplate\n\tstruct tuple_cat_helper {\n\t\tusing tuple_index_seq = std::index_sequence;\n\t\tusing tuple_size_seq = std::index_sequence::value...>;\n\n\t\tusing result_index_seq = std::make_index_sequence::value...>::value>;\n\n\t\tusing outer_index_seq = expand_t>;\n\t\tusing inner_index_seq = minus_seq_t>>;\n\t\tusing result_type\t = tuple_cat_result_t;\n\t};\n\ttemplate\n\tconstexpr decltype(auto) tuple_cat_impl(std::index_sequence, std::index_sequence, Tuple&& tup) {\n\t\treturn R {get(get(tup))...};\n\t}\n}// namespace meta_impl\n\ntemplate::type...>, typename R = typename H::result_type>\nconstexpr R tuple_cat(Ts&&... tuples) {\n\treturn meta_impl::tuple_cat_impl(typename H::outer_index_seq {}, typename H::inner_index_seq {}, tuple_forward(std::forward(tuples)...));\n}\n\n/// legacy\n// template \n// using TupleAttribType = std::decay_t>;\n\ntemplate\nstruct tuple_type_list {\n\ttemplate\n\tusing type = typename std::tuple_element::type;\n};\n\ntemplate\nusing TupleAttribType = std::decay_t::template type>;\n\ntemplate\nconstexpr decltype(auto) gen_uniform_tuple(std::index_sequence) {\n\tusing Tuple = std::tuple= 0, T>...>;\n\treturn Tuple {};\n};\n\ntemplate\nusing UniformTuple = decltype(gen_uniform_tuple>(std::make_index_sequence {}));\n\ntemplate\nstruct tupleOffset;\n\ntemplate\nstruct tupleOffset {\n\tstatic constexpr std::size_t value = tupleOffset::value + sizeof(TupleAttribType);\n};\ntemplate\nstruct tupleOffset<0, Tuple> {\n\tstatic constexpr std::size_t value = 0;\n};\n\ntemplate\nconstexpr void gen_tuple_offsets_impl(std::array& offsets, std::index_sequence) {\n\t(void) std::initializer_list {(offsets[Is] = tupleOffset::value, 0)...};\n}\n\ntemplate\nconstexpr auto gen_tuple_offsets() {\n\tauto tuplesize = std::tuple_size::value;\n\tstd::array::value> offsets;\n\tusing Indices = std::make_index_sequence::value>;\n\tgen_tuple_offsets_impl(offsets, Indices {});\n\treturn offsets;\n}\n\ntemplate\nvoid forIndexAlloc(Func&& f, std::index_sequence) {\n\treturn (void) std::initializer_list {(std::forward(f)(std::forward(I), sizeof(TupleAttribType)), 0)...};\n}\n\n/// tuple functionality\ntemplate\nvoid forArgs(Func&& f, Args&&... args) {\n\treturn (void) std::initializer_list {(f(std::forward(args)), 0)...};\n}\n\ntemplate\ndecltype(auto) apply_impl(F&& f, Tuple t, std::index_sequence) {\n\treturn std::forward(f)(std::get(std::forward(t))...);\n}\n\ntemplate\ndecltype(auto) apply(F&& f, Tuple t) {\n\tusing Indices = std::make_index_sequence>::value>;\n\treturn apply_impl(std::forward(f), std::forward(t), Indices {});\n}\n\ntemplate\nvoid forTuple(Func&& f, Tpl&& tpl) {\n\tapply(\n\t\t[&f](auto&&... xs) {\n\t\t\tforArgs(f, std::forward(xs)...);\n\t\t},\n\t\tstd::forward(tpl)\n\t);\n}\n\ntemplate\nconstexpr decltype(auto) gen_uniform_channel_tuple(std::index_sequence) {\n\t// static_assert((sizeof(T) & 0x3) == 0);\n\tusing Tuple = std::tuple, T>...>;\n\treturn Tuple {};\n};\n\n}// namespace mn\n\n#endif\n" }, { "path": "Library/MnBase/Meta/TypeDecoration.h", "content": "#ifndef TYPE_DECORATION_H\n#define TYPE_DECORATION_H\n\n#include \"Meta.h\"\n\nnamespace mn {\n\n/// decay\n/// const, volatile, reference, pointer, sign, extent\ntemplate\nusing add_const_t = const T;\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Meta/TypeIdentity.h", "content": "#ifndef TYPE_IDENTITY_H\n#define TYPE_IDENTITY_H\n\n#include \"Meta.h\"\n\nnamespace mn {\n\n/// primary type\nstruct {\n\t;\n};\n\n/// composite type\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Meta/TypeMeta.h", "content": "#ifndef TYPE_META_H\n#define TYPE_META_H\n\n#include \n#include \n#include \n\n#include \"MnBase/Reflection.h\"\n\nnamespace mn {\n\n/// https://zh.cppreference.com/w/cpp/utility/tuple/make_tuple\ntemplate\nstruct unwrap_refwrapper {\n\tusing type = T;\n};\n\ntemplate\nstruct unwrap_refwrapper> {\n\tusing type = T&;\n};\n\ntemplate\nusing special_decay_t = typename unwrap_refwrapper>::type;\n\n/// indexable type list to avoid recursion\nnamespace meta_impl {\n\ttemplate\n\tstruct type_wrapper {\n\t\tusing type = T;\n\t};\n\n\ttemplate\n\tstruct indexed_type {\n\t\tusing type = T;\n\t};\n\n\ttemplate\n\tstruct indexed_types;\n\n\ttemplate\n\tstruct indexed_types, Ts...> : indexed_type... {};\n\n\t/// use pointer rather than reference as in taocpp! [incomplete type error]\n\ttemplate\n\tindexed_type extract_type(indexed_type*);\n}// namespace meta_impl\n\ntemplate\nstruct type_seq {\n\tusing indices = std::index_sequence_for;\n\ttemplate\n\tusing type = typename decltype(meta_impl::extract_type(std::add_pointer_t> {}))::type;\n};\ntemplate\nstruct type_seq> {\n\tusing indices = std::make_index_sequence;\n\ttemplate\n\tusing type = typename decltype(meta_impl::extract_type(std::add_pointer_t...>> {}))::type;\n};\n\n/// select type by index\ntemplate\nusing select_indexed_type = typename type_seq::template type;\ntemplate\nusing select_type = typename TypeSeq::template type;\n\n/// select (constant integral) value (integral_constant) by index\ntemplate\nusing select_indexed_value = select_indexed_type...>;\ntemplate\nusing select_value = typename type_seq::template type;\n\n/// reverse seq\nnamespace meta_impl {\n\ttemplate\n\tstruct reverse_type_seq_impl;\n\n\ttemplate\n\tstruct reverse_type_seq_impl, type_seq> {\n\t\tstatic_assert(sizeof...(Is) == sizeof...(Ts), \"reverse_type_seq_impl error\");\n\t\tusing type = type_seq::template type...>;\n\t};\n\n\ttemplate\n\tstruct reverse_value_seq_impl;\n\n\ttemplate\n\tstruct reverse_value_seq_impl, std::integer_sequence> {\n\t\tstatic_assert(sizeof...(Is) == sizeof...(Ns), \"reverse_value_seq_impl error\");\n\t\tusing type = std::integer_sequence...>::template type {})...>;\n\t};\n}// namespace meta_impl\n\ntemplate\nusing type_seq_rev = typename meta_impl::reverse_type_seq_impl, type_seq>::type;\n\ntemplate\nstruct rev_type_seq_impl;\ntemplate\nstruct rev_type_seq_impl> {\n\tusing type = typename meta_impl::reverse_type_seq_impl, type_seq>::type;\n};\ntemplate\nusing rev_type_seq = typename rev_type_seq_impl::type;\n\ntemplate\nusing value_seq_rev = typename meta_impl::reverse_value_seq_impl, std::integer_sequence>::type;\n\ntemplate\nstruct rev_value_seq_impl;\ntemplate\nstruct rev_value_seq_impl> {\n\tusing type = typename meta_impl::reverse_value_seq_impl, std::integer_sequence>::type;\n};\ntemplate\nusing rev_value_seq = typename rev_value_seq_impl::type;\n\n/// legacy\ntemplate\nstruct type_list {\n\tusing Indices = std::make_integer_sequence;\n\tusing types\t = std::tuple...>;\n\ttemplate\n\tusing type\t\t\t\t\t= typename std::tuple_element::type;\n\tstatic constexpr auto count = sizeof...(Ts);\n\tstatic constexpr auto size\t= sizeof(types);// wrong: std::tuple_size::value;\n\t\t\t\t\t\t\t\t\t\t\t\t// template \n\t\t\t\t\t\t\t\t\t\t\t\t// static constexpr auto offset = tupleOffset::value;\n\t\t\t\t\t\t\t\t\t\t\t\t// using Indices = ;\n};\n\ntemplate\nusing AttribType = typename type_seq::template type;\n\n//TODO: Avoid confusion with std::placeholders\nnamespace placeholder {\n\tusing placeholder_type = unsigned;\n\tconstexpr auto _0\t = std::integral_constant {};\n\tconstexpr auto _1\t = std::integral_constant {};\n\tconstexpr auto _2\t = std::integral_constant {};\n\tconstexpr auto _3\t = std::integral_constant {};\n\tconstexpr auto _4\t = std::integral_constant {};\n\tconstexpr auto _5\t = std::integral_constant {};\n\tconstexpr auto _6\t = std::integral_constant {};\n\tconstexpr auto _7\t = std::integral_constant {};\n\tconstexpr auto _8\t = std::integral_constant {};\n\tconstexpr auto _9\t = std::integral_constant {};\n\tconstexpr auto _10\t = std::integral_constant {};\n\tconstexpr auto _11\t = std::integral_constant {};\n\tconstexpr auto _12\t = std::integral_constant {};\n\tconstexpr auto _13\t = std::integral_constant {};\n\tconstexpr auto _14\t = std::integral_constant {};\n\tconstexpr auto _15\t = std::integral_constant {};\n\tconstexpr auto _16\t = std::integral_constant {};\n\tconstexpr auto _17\t = std::integral_constant {};\n\tconstexpr auto _18\t = std::integral_constant {};\n\tconstexpr auto _19\t = std::integral_constant {};\n\tconstexpr auto _20\t = std::integral_constant {};\n\tconstexpr auto _21\t = std::integral_constant {};\n\tconstexpr auto _22\t = std::integral_constant {};\n\tconstexpr auto _23\t = std::integral_constant {};\n\tconstexpr auto _24\t = std::integral_constant {};\n\tconstexpr auto _25\t = std::integral_constant {};\n\tconstexpr auto _26\t = std::integral_constant {};\n\tconstexpr auto _27\t = std::integral_constant {};\n\tconstexpr auto _28\t = std::integral_constant {};\n\tconstexpr auto _29\t = std::integral_constant {};\n\tconstexpr auto _30\t = std::integral_constant {};\n\tconstexpr auto _31\t = std::integral_constant {};\n}// namespace placeholder\nusing place_id = typename placeholder::placeholder_type;\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Meta/TypeOperation.h", "content": "#ifndef TYPE_OPERATION_H\n#define TYPE_OPERATION_H\n\n#include \"Meta.h\"\n\nnamespace mn {\n\ntemplate\nstruct is_iterable : std::false_type {};\ntemplate\nstruct is_iterable())), decltype(*std::end(std::declval()))>> : std::true_type {};\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Meta/TypeProperty.h", "content": "#ifndef TYPE_PROPERTY_H\n#define TYPE_PROPERTY_H\n\n#include \"Meta.h\"\n\nnamespace mn {\n\nstruct {\n\t;\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Object/Function.h", "content": "#ifndef FUNCTION_H\n#define FUNCTION_H\n#include \n#include \n#include \n\n#include \"MnBase/Meta/TypeMeta.h\"\n\nnamespace mn {\n\n//typename \n//using func_ref = tl::function_ref;\n\ntemplate\nstruct FunctionTraits;\n\ntemplate\nstruct FunctionTraits> {\n\tstatic constexpr std::size_t nargs = sizeof...(Args);\n\n\tusing resultType = R;\n\n\ttemplate\n\tusing argType = AttribType;\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Object/Property.h", "content": "#ifndef PROPERTY_H\n#define PROPERTY_H\n\n#include \n\nnamespace mn {\n\nstruct NonCopyable {\n\tNonCopyable()\t\t\t\t\t\t\t = default;\n\tNonCopyable(const NonCopyable&)\t\t\t = delete;\n\tNonCopyable& operator=(const NonCopyable&) = delete;\n};\n\ntemplate\nstruct is_base_of;\ntemplate\nstruct is_base_of {\n\tstatic_assert(std::is_base_of::value, \"T is not a subclass of Base!\");\n};\ntemplate\nstruct is_base_of : public is_base_of {\n\tstatic_assert(std::is_base_of::value, \"T is not a subclass of Base!\");\n};\n\ntemplate class Feature, typename... Ts>\nstruct satisfy;\ntemplate class Feature, typename T>\nstruct satisfy {\n\tstatic_assert(Feature::value, \"T does not satisfy the feature!\");\n};\ntemplate class Feature, typename T, typename... Ts>\nstruct satisfy : public satisfy {\n\tstatic_assert(Feature::value, \"T does not satisfy the feature!\");\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Object/Structural.h", "content": "#ifndef STRUCTURAL_H\n#define STRUCTURAL_H\n\n#include \n#include \n#include \n\n#include \"Function.h\"\n#include \"MnBase/Meta/ControlFlow.h\"\n#include \"MnBase/Meta/MathMeta.h\"\n#include \"MnBase/Meta/Polymorphism.h\"\n#include \"MnBase/Meta/TypeMeta.h\"\n#include \"Property.h\"\n#include \"StructuralAuxiliary.h\"\n#include \"StructuralDeclaration.h\"\n\nnamespace mn {\n\nenum class StructuralComponentIndex : std::size_t {\n\tHANDLE_PTR = 0,\n\tPARENT_SCOPE_HANDLE,\n\tACTIVE_MASK///< for on-demand allocation\n};\n\nusing ci = StructuralComponentIndex;\n\n/// cuda forbids ci as int_seq type\nusing orphan_signature\t\t = std::integer_sequence(StructuralComponentIndex::HANDLE_PTR)>;\nusing standard_signature\t = std::integer_sequence(StructuralComponentIndex::PARENT_SCOPE_HANDLE)>;\nusing sparse_orphan_signature = std::integer_sequence(StructuralComponentIndex::ACTIVE_MASK)>;\n\n/// instance related declarations\ntemplate\nstruct StructuralInstance;\ntemplate\nusing Instance = StructuralInstance, (attrib_index) 0, Signature>;\n\ntemplate\nstruct StructuralInstanceTraits : ParentInstance::attribs::template type<(std::size_t) AttribNo> {\n\tusing self\t\t\t = typename ParentInstance::attribs::type<(std::size_t) AttribNo>;\n\tusing parent_indexer = typename ParentInstance::domain::index;\n\tusing self_indexer\t = typename self::domain::index;\n};\n\ntemplate\nstruct StructuralInstanceComponent;\ntemplate\nstruct StructuralInstanceComponent {};\ntemplate\nstruct StructuralInstanceComponent {\n\ttypename StructuralInstanceTraits::ParentInstance _parent;\n\ttypename StructuralInstanceTraits::parent_indexer _index;\n};\ntemplate\nstruct StructuralInstanceComponent {\n\tstatic_assert(sizeof(char) == 1, \"size (byte) of char is not 1.\");\n\tchar* active_mask;\n};\n\ntemplate\nstruct StructuralInstance>\n\t: StructuralInstanceTraits\n\t, StructuralInstanceComponent(Cs)>... {\n\tusing traits\t\t= StructuralInstanceTraits;\n\tusing component_seq = std::integer_sequence;\n\tusing self_instance = StructuralInstance;\n\ttemplate\n\tusing accessor = typename traits::template Accessor;\n\n\t// hierarchy traverse\n\ttemplate\n\tconstexpr auto chfull(std::integral_constant, Indices&&... indices) const {\n\t\tStructuralInstance ret {};\n\t\tret._parent = *this;\n\t\tret._index\t= traits::self_indexer(std::forward(indices)...);\n\t\tret.handle\t= MemResource {reinterpret_cast(this->handle.ptrval + accessor::coord_offset(std::forward(indices)...))};\n\t\treturn ret;\n\t}\n\ttemplate\n\tconstexpr auto ch(std::integral_constant, Indices&&... indices) const {\n\t\tStructuralInstance ret {};\n\t\tret.handle = MemResource {reinterpret_cast(this->handle.ptrval + accessor::coord_offset(std::forward(indices)...))};\n\t\treturn ret;\n\t}\n\ttemplate\n\tconstexpr auto chptr(std::integral_constant, Indices&&... indices) const {\n\t\tStructuralInstance ret {};\n\t\tret.handle.ptrval = *reinterpret_cast(this->handle.ptrval + accessor::coord_offset(std::forward(indices)...));\n\t\treturn ret;\n\t}\n};\n\n/// initialization\ntemplate\nconstexpr auto spawn(Allocator allocator) {\n\tauto ret = Instance {};\n\tret.allocate_handle(allocator);\n\treturn ret;\n}\ntemplate\nconstexpr auto spawn(Allocator allocator, std::size_t size) {\n\tauto ret = Instance {};\n\tret.allocate_handle(allocator, size);\n\treturn ret;\n}\ntemplate\nconstexpr void recycle(Instance& instance, Allocator allocator) {\n\tinstance.deallocate(allocator);\n}\n\n/// common notation\nusing empty_ = StructuralEntity;\nusing i64_\t = StructuralEntity;\nusing u64_\t = StructuralEntity;\nusing f64_\t = StructuralEntity;\nusing i32_\t = StructuralEntity;\nusing u32_\t = StructuralEntity;\nusing f32_\t = StructuralEntity;\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Object/StructuralAuxiliary.h", "content": "#ifndef STRUCTURAL_AUXILIARY_H\n#define STRUCTURAL_AUXILIARY_H\n#include \"MnBase/Math/Vec.h\"\n#include \"MnBase/Meta/MathMeta.h\"\n\nnamespace mn {\n\nstruct MemoryLayout {\n\tenum class element : unsigned char {\n\t\tAOS = 0,\n\t\tSOA = 1\n\t};\n};\nenum class StructuralAllocationPolicy : std::size_t {\n\tFULL_ALLOCATION = 0,\n\tON_DEMAND\t\t= 1,\n\tTOTAL\n};\nenum class StructuralPaddingPolicy : std::size_t {\n\tCOMPACT\t\t = 0,\n\tSUM_POW2_ALIGN = 1,\n\tMAX_POW2_ALIGN = 2,\n\tTOTAL\n};\n\nusing attrib_layout = MemoryLayout::element;\n\nstruct IdentityDecorator {};\n\ntemplate\nstruct Decorator : IdentityDecorator {\n\tstatic constexpr auto alloc_policy\t = AllocPolicy;\n\tstatic constexpr auto padding_policy = PaddingPolicy;\n};\n\nstruct IdentityStructuralIndex {};\n\ntemplate\nstruct CompactDomain\n\t: IdentityStructuralIndex\n\t, indexer {\n\tusing base_t = indexer;\n\tusing index\t = vec;\n};\n\ntemplate\nusing AlignedDomain = CompactDomain::value...>;\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Object/StructuralDeclaration.h", "content": "#ifndef STRUCTURAL_DECLARATION_H\n#define STRUCTURAL_DECLARATION_H\n#include \n\n#include \"MnBase/Math/Vec.h\"\n#include \"MnBase/Memory/MemObj.h\"\n#include \"MnBase/Meta/MathMeta.h\"\n\nnamespace mn {\n\nenum class StructuralType : std::size_t {\n\t/// no child\n\tSENTINEL = 0,\n\tENTITY\t = 1,\n\t/// with child\n\tHASH\t= 2,\n\tDENSE\t= 3,\n\tDYNAMIC = 4,\n\tBINARY\t= 5,\n\tTOTAL\n};\nusing attrib_index = place_id;\n\nstruct IdentityStructural {};\n\ntemplate\nstruct Structural;\n\ntemplate\nstruct StructuralTraits {\n\tstatic constexpr StructuralType node_type\t = NodeType;\n\tstatic constexpr attrib_layout elementLayout = Layout;\n\n\tusing decoration = Decoration;\n\tusing domain\t = Domain;\n\tusing attribs\t = type_seq;\n\tusing self\t\t = Structural;\n\tusing vt\t\t = void*;///< should be hidden by Structural ENTITY\n\ttemplate\n\tusing value_type = select_indexed_type;\n\n\tstatic constexpr auto attrib_count\t\t = attribs::indices::size();\n\tstatic constexpr std::size_t element_size = select_indexed_value<\n\t\t(std::size_t) decoration::padding_policy,\n\t\tstd::size_t,\n\t\t// compact\n\t\tintegral_seq_sum::value,\n\t\t// sum aligned\n\t\tnext_2pow::value>::value,\n\t\t// max aligned\n\t\t(integral_seq_max::value)...>::value) * sizeof...(Structurals)>::value;\n\tstatic constexpr std::size_t element_storage_size = select_indexed_value<\n\t\t(std::size_t) decoration::alloc_policy,\n\t\tstd::size_t,\n\t\t/// full-allocation\n\t\telement_size,\n\t\t/// on-demand\n\t\tsizeof(void*) * sizeof...(Structurals)>::value;\n\t/// for allocation\n\tstatic constexpr std::size_t size = domain::extent * element_storage_size;\n\t// SOA -> multipool, AOS -> pool\n\n\ttemplate\n\tstruct Accessor {\n\t private:\n\t\tstatic constexpr uintptr_t element_stride_in_bytes_func() {\n\t\t\tswitch(decoration::alloc_policy) {\n\t\t\t\tcase StructuralAllocationPolicy::FULL_ALLOCATION:\n\t\t\t\t\treturn (elementLayout == attrib_layout::AOS ? element_storage_size : attribs::template type<(std::size_t) AttribNo>::size);\n\t\t\t\tcase StructuralAllocationPolicy::ON_DEMAND:\n\t\t\t\t\treturn sizeof(void*) * (elementLayout == attrib_layout::AOS ? sizeof...(Structurals) : 1);\n\t\t\t\tdefault:\n\t\t\t\t\treturn 0;\n\t\t\t}\n\t\t}\n\t\tstatic constexpr uintptr_t attrib_base_offset_func() {\n\t\t\tswitch(decoration::alloc_policy) {\n\t\t\t\tcase StructuralAllocationPolicy::FULL_ALLOCATION:\n\t\t\t\t\treturn (elementLayout == attrib_layout::AOS ? 1 : domain::extent) * excl_prefix_sum<(std::size_t) AttribNo, std::integer_sequence>::value;\n\t\t\t\tcase StructuralAllocationPolicy::ON_DEMAND:\n\t\t\t\t\treturn (elementLayout == attrib_layout::AOS ? 1 : domain::extent) * (std::size_t) AttribNo * sizeof(void*);\n\t\t\t\tdefault:\n\t\t\t\t\treturn 0;\n\t\t\t}\n\t\t}\n\n\t public:\n\t\tstatic constexpr uintptr_t element_stride_in_bytes = element_stride_in_bytes_func();\n\n\t\tstatic constexpr uintptr_t attrib_base_offset = attrib_base_offset_func();\n\t\ttemplate\n\t\tstatic constexpr uintptr_t coord_offset(Indices&&... is) noexcept {\n\t\t\treturn attrib_base_offset + domain::offset(std::forward(is)...) * element_stride_in_bytes;\n\t\t}\n\t\ttemplate\n\t\tstatic constexpr uintptr_t linear_offset(Index&& i) noexcept {\n\t\t\treturn attrib_base_offset + std::forward(i) * element_stride_in_bytes;\n\t\t}\n\t};\n\n\tMemResource handle;\n\n\t// memory manage\n\ttemplate\n\tvoid allocate_handle(Allocator allocator) {\n\t\tif(self::size != 0) {\n\t\t\thandle.ptr = allocator.allocate(self::size);\n\t\t} else {\n\t\t\thandle.ptr = nullptr;\n\t\t}\n\t}\n\ttemplate\n\tvoid allocate_handle(Allocator allocator, std::size_t s) {\n\t\tif(s != 0) {\n\t\t\thandle.ptr = allocator.allocate(s);\n\t\t} else {\n\t\t\thandle.ptr = nullptr;\n\t\t}\n\t}\n\n\ttemplate\n\tvoid deallocate(Allocator allocator) {\n\t\tallocator.deallocate(handle.ptr, self::size);\n\t\thandle.ptr = nullptr;\n\t}\n\ttemplate\n\tvoid deallocate(Allocator allocator, std::size_t s) {\n\t\tallocator.deallocate(handle.ptr, s);\n\t\thandle.ptr = nullptr;\n\t}\n\n\t// value access\n\ttemplate, typename... Indices>\n\tconstexpr auto& val(std::integral_constant, Indices&&... indices) {\n\t\treturn *reinterpret_cast(handle.ptrval + Accessor::coord_offset(std::forward(indices)...));\n\t}\n\ttemplate>\n\tconstexpr auto& val(std::integral_constant) {\n\t\treturn *reinterpret_cast(handle.ptrval + Accessor::attrib_base_offset);\n\t}\n\ttemplate, typename... Indices>\n\tconstexpr const auto& val(std::integral_constant, Indices&&... indices) const {\n\t\treturn *reinterpret_cast(handle.ptrval + Accessor::coord_offset(std::forward(indices)...));\n\t}\n\ttemplate>\n\tconstexpr const auto& val(std::integral_constant) const {\n\t\treturn *reinterpret_cast(handle.ptrval + Accessor::attrib_base_offset);\n\t}\n\n\ttemplate, typename Index>\n\tconstexpr auto& val_1d(std::integral_constant, Index&& index) {\n\t\treturn *reinterpret_cast(handle.ptrval + Accessor::linear_offset(std::forward(index)));\n\t}\n\ttemplate, typename Index>\n\tconstexpr const auto& val_1d(std::integral_constant, Index&& index) const {\n\t\treturn *reinterpret_cast(handle.ptrval + Accessor::linear_offset(std::forward(index)));\n\t}\n};\n\n/// root\ntemplate\nstruct RootInstance\n\t: IdentityStructural\n\t, StructuralTraits, CompactDomain, attrib_layout::AOS, Structural> {\n\t/// purely for its domain and attrib info query, i.e. Structural info\n\tusing vt = void*;\n};\n/// ENTITY\ntemplate\nstruct StructuralEntity : IdentityStructural {\n\tstatic constexpr std::size_t size = sizeof(T);\n\n\tusing vt\t = T;\n\tusing domain = AlignedDomain;\n};\ntemplate<>\nstruct StructuralEntity : IdentityStructural {\n\tstatic constexpr std::size_t size = 0;\n\n\tusing vt\t = void;\n\tusing domain = AlignedDomain;// int[0] is allowed in c++\n};\n/// HASH\ntemplate\nstruct Structural\n\t: IdentityStructural\n\t, StructuralTraits {\n\tusing base_t\t\t\t\t\t = StructuralTraits;\n\tusing CheckPrerequisite\t\t\t = void_t, is_base_of, is_base_of, satisfy>;\n\tusing key_t\t\t\t\t\t\t = vec;\n\tusing value_t\t\t\t\t\t = typename Domain::index_type;\n\tstatic constexpr auto sentinel_v = value_t(-1);\n\n\t// data members\n\tvalue_t capacity;\n\tvalue_t* count;\n\tkey_t* active_keys;\t //\n\tvalue_t* index_table;//\n\n\t// func members\n\ttemplate\n\tvoid allocate_table(Allocator allocator, value_t capacity) {\n\t\tthis->capacity = capacity;\n\t\tcount\t\t = static_cast(allocator.allocate(sizeof(value_t)));\n\t\tactive_keys\t = static_cast(allocator.allocate(sizeof(key_t) * capacity));\n\t\t/// lookup table\n\t\tindex_table = static_cast(allocator.allocate(sizeof(value_t) * Domain::extent));\n\t}\n\n\ttemplate\n\tvoid resize_table(Allocator allocator, std::size_t capacity) {\n\t\tallocator.deallocate(active_keys, this->capacity);\n\t\tactive_keys\t = static_cast(allocator.allocate(sizeof(key_t) * capacity));\n\t\tthis->capacity = capacity;\n\t}\n\n\ttemplate\n\tvoid deallocate(Allocator allocator) {\n\t\tallocator.deallocate(count, sizeof(value_t));\n\t\tallocator.deallocate(active_keys, sizeof(key_t) * capacity);\n\t\tallocator.deallocate(index_table, sizeof(value_t) * Domain::extent);\n\t\tbase_t::deallocate(allocator);\n\t\tcapacity\t= 0;\n\t\tcount\t\t= nullptr;\n\t\tactive_keys = nullptr;\n\t\tindex_table = nullptr;\n\t}\n\n\t//TODO: Add (optional) range checks here (and maybe elsewhere too)\n\ttemplate\n\tconstexpr auto& val(Indices&&... indices) {\n\t\treturn *static_cast(static_cast(index_table + Domain::offset(std::forward(indices)...)));\n\t}\n\n\ttemplate\n\tconstexpr auto& index_impl(key_t& coord, std::index_sequence) {\n\t\treturn *static_cast(static_cast(index_table + Domain::offset((coord[Is])...)));\n\t}\n\n\tconstexpr auto& index(key_t coord) {\n\t\treturn index_impl(coord, std::make_index_sequence {});\n\t}\n\n\ttemplate\n\tconstexpr const auto& index_impl(key_t& coord, std::index_sequence) const {\n\t\treturn *static_cast(static_cast(index_table + Domain::offset((coord[Is])...)));\n\t}\n\n\tconstexpr const auto& index(key_t coord) const {\n\t\treturn index_impl(coord, std::make_index_sequence {});\n\t}\n};\n/// DENSE\ntemplate\nstruct Structural\n\t: IdentityStructural\n\t, StructuralTraits {\n\tusing base_t\t\t\t= StructuralTraits;\n\tusing CheckPrerequisite = void_t, is_base_of, is_base_of, satisfy>;\n};\n\n/// DYNAMIC\ntemplate\nstruct Structural\n\t: IdentityStructural\n\t, StructuralTraits {\n\tusing base_t\t\t\t= StructuralTraits;\n\tusing CheckPrerequisite = void_t, is_base_of, is_base_of, satisfy, enable_if_t>;\n\tusing value_t\t\t\t= unsigned long long int;\n\n\tstd::size_t capacity;\n\n\ttemplate\n\tvoid allocate_handle(Allocator allocator, std::size_t capacity = Domain::extent) {\n\t\tif(capacity != 0) {\n\t\t\tthis->handle.ptr = allocator.allocate(capacity * base_t::element_storage_size);\n\t\t} else {\n\t\t\tthis->handle.ptr = nullptr;\n\t\t}\n\t\tthis->capacity = capacity;\n\t}\n\n\ttemplate\n\tvoid resize(Allocator allocator, std::size_t capacity) {\n\t\tallocator.deallocate(this->handle.ptr, this->capacity);\n\t\tthis->capacity\t = capacity;///< each time multiply by 2\n\t\tthis->handle.ptr = allocator.allocate(capacity * base_t::element_storage_size);\n\t}\n\n\ttemplate\n\tvoid deallocate(Allocator allocator) {\n\t\tallocator.deallocate(this->handle.ptr, this->capacity * base_t::element_storage_size);\n\t\tthis->capacity\t = 0;\n\t\tthis->handle.ptr = nullptr;\n\t}\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Profile/CppTimers.hpp", "content": "#ifndef CPP_TIMERS_HPP\n#define CPP_TIMERS_HPP\n\n#include \n#include \n\n#include \n\nnamespace mn {\n\nstruct CppTimer {\n\tusing HRC\t\t= std::chrono::high_resolution_clock;\n\tusing NS\t\t= std::chrono::nanoseconds;///< default timer unit\n\tusing TimeStamp = HRC::time_point;\n\n private:\n\tTimeStamp last;\n\tTimeStamp cur;\n\n public:\n\tvoid tick() {\n\t\tlast = HRC::now();\n\t}\n\n\tvoid tock() {\n\t\tcur = HRC::now();\n\t}\n\n\tfloat elapsed() {\n\t\tfloat duration = std::chrono::duration_cast(cur - last).count() * 1e-6;\n\t\treturn duration;\n\t}\n\n\tvoid tock(std::string tag) {\n\t\ttock();\n\t\tfmt::print(fg(fmt::color::cyan), \"{}: {} ms\\n\", tag.c_str(), elapsed());\n\t}\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Profile/CudaTimers.cuh", "content": "#ifndef CUDA_TIMERS_CUH\n#define CUDA_TIMERS_CUH\n\n#include \n#include \n#include \n\nnamespace mn {\n\nstruct CudaTimer {\n\tusing TimeStamp = cudaEvent_t;\n\n private:\n\tcudaStream_t stream_id;\n\tTimeStamp last;\n\tTimeStamp cur;\n\n public:\n\texplicit CudaTimer(cudaStream_t sid)\n\t\t: stream_id {sid} {\n\t\tcudaEventCreate(&last);\n\t\tcudaEventCreate(&cur);\n\t}\n\n\t~CudaTimer() {\n\t\tcudaEventDestroy(last);\n\t\tcudaEventDestroy(cur);\n\t}\n\n\tvoid tick() {\n\t\tcudaEventRecord(last, stream_id);\n\t}\n\n\tvoid tock() {\n\t\tcudaEventRecord(cur, stream_id);\n\t}\n\n\tfloat elapsed() {\n\t\tfloat duration;\n\t\tcudaEventSynchronize(cur);\n\t\tcudaEventElapsedTime(&duration, last, cur);\n\t\treturn duration;\n\t}\n\n\tvoid tock(std::string tag) {\n\t\ttock();\n\t\tfmt::print(fg(fmt::color::cyan), \"{}: {} ms\\n\", tag.c_str(), elapsed());\n\t}\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnBase/Reflection.h", "content": "#ifndef REFLECTION_H\n#define REFLECTION_H\n\n#include \n\nnamespace mn {\n\n/// compile-time type inspection\ntemplate\nclass that_type;\n\ntemplate\nvoid name_that_type(T& param) {\n\tthat_type tType;\n\tthat_type paramType;\n}\n\n/// runtime\n//typeid(x).name()\ntemplate\nconstexpr decltype(auto) query_type_name(T&& x) {\n\treturn typeid(std::forward(x)).name();\n}\n\n}// namespace mn\n\n#endif\n" }, { "path": "Library/MnBase/Singleton.h", "content": "#ifndef SINGLETON_H\n#define SINGLETON_H\n\n#include \n// http ://www.boost.org/doc/libs/1_39_0/boost/pool/detail/singleton.hpp\n\nnamespace mn {\n\n/*\n *\t@note\tSingleton\n */\n// T must be: no-throw default constructible and no-throw destructible\ntemplate\nstruct Singleton {\n public:\n\tstatic T& instance() {\n\t\tstatic T instance {};\n\t\treturn instance;\n\t}\n};\n\n/*\n *\t\\class\tManagedSingleton\n *\t\\note\tUsed in global systems\n */\ntemplate\nstruct ManagedSingleton {\n protected:\n\tstatic T* p_instance;//NOLINT(cppcoreguidelines-avoid-non-const-global-variables) Cannot avoid this\n\n public:\n\tstatic void startup() {\n\t\tassert(p_instance == nullptr);\n\t\tp_instance = new T();\n\t}\n\tstatic void shutdown() {\n\t\tassert(p_instance != nullptr);\n\t\tdelete p_instance;\n\t}\n\n\t///\n\tT* operator->() {\n\t\treturn p_instance;\n\t}\n\n\tstatic T& instance() {\n\t\tassert(p_instance != nullptr);\n\t\treturn *p_instance;\n\t}\n\tstatic T* get_instance() {\n\t\tassert(p_instance != nullptr);\n\t\treturn p_instance;\n\t}\n\tstatic const T* get_const_instance() {\n\t\tassert(p_instance != nullptr);\n\t\treturn p_instance;\n\t}\n};\n\ntemplate\nT* ManagedSingleton::p_instance = nullptr;//NOLINT(cppcoreguidelines-avoid-non-const-global-variables) Cannot avoid this\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnSystem/CMakeLists.txt", "content": "include(sourcelist.cmake)\n\n# build: PRIVATE, usage: INTERFACE, both: PUBLIC.\nif (CUDA_FOUND)\n\tadd_cuda_library(mncuda)\n\t\n\ttarget_include_directories(mncuda\n\t\tPUBLIC ${PROJECT_SOURCE_DIR}/Library\n\t)\n\t\n\ttarget_sources(mncuda\n\t\tPRIVATE\t${CudaSystemSrc}\n\t)\n\t\n\ttarget_precompile_headers(mncuda \n\t\tINTERFACE\tCuda/Cuda.h\n\t\t\t\t\tCuda/DeviceUtils.cuh\n\t\t\t\t\tCuda/HostUtils.hpp\n\t)\n\nendif()\n\nadd_library(mnio)\n\nset_target_properties(mnio\n PROPERTIES #CXX_STANDARD 20\n #LINKER_LANGUAGE CXX\n POSITION_INDEPENDENT_CODE ON\n)\n\ntarget_include_directories(mnio\n\tPUBLIC ${PROJECT_SOURCE_DIR}/Library\n)\n\ntarget_compile_definitions(mnio\n INTERFACE AssetDirPath=\"${PROJECT_SOURCE_DIR}/Data/\"\n)\n\ntarget_sources(mnio \n PRIVATE IO/IO.cpp\n)\n\ntarget_precompile_headers(mnio \n INTERFACE IO/IO.h\n)\n\ntarget_link_libraries(mnio \n PUBLIC partio\n)\n" }, { "path": "Library/MnSystem/Cuda/Allocators.cuh", "content": "#ifndef ALLOCATORS_CUH\n#define ALLOCATORS_CUH\n#include \n\n#include \n#include \n\n#include \"HostUtils.hpp\"\n#include \"MnBase/Memory/Allocator.h\"\n\nnamespace mn {\n\nstruct DeviceMemoryResource\n\t: Singleton\n\t, MemoryResource {\n\tstatic constexpr size_t MAX_ALIGNMENT = 256;\n\n\tDeviceMemoryResource() = default;\n\n\tvoid* do_allocate(std::size_t bytes, std::size_t alignment) {//NOLINT(readability-convert-member-functions-to-static) Method is designed to be a non-static class member\n\t\tif(alignment > MAX_ALIGNMENT) {\n\t\t\tthrow std::bad_alloc {};\n\t\t}\n\t\tvoid* ret;\n\t\tif(cudaMalloc((void**) &ret, bytes) != cudaSuccess) {\n\t\t\tthrow std::bad_alloc {};\n\t\t}\n\t\treturn ret;\n\t}\n\n\tvoid do_deallocate(void* ptr, std::size_t bytes, std::size_t alignment) {//NOLINT(readability-convert-member-functions-to-static) Method is designed to be a non-static class member\n\t\t(void) bytes;\n\t\t(void) alignment;\n\n\t\tif(cudaFree(ptr) != cudaSuccess) {\n\t\t\tthrow std::bad_alloc {};\n\t\t}\n\t}\n};\n\nstruct UnifiedMemoryResource\n\t: Singleton\n\t, MemoryResource {\n\tstatic constexpr size_t MAX_ALIGNMENT = 256;\n\n\tUnifiedMemoryResource() = default;\n\n\tvoid* do_allocate(std::size_t bytes, std::size_t alignment) {//NOLINT(readability-convert-member-functions-to-static) Method is designed to be a non-static class member\n\t\tif(alignment > MAX_ALIGNMENT) {\n\t\t\tthrow std::bad_alloc {};\n\t\t}\n\t\tvoid* ret;\n\t\tif(cudaMallocManaged((void**) &ret, bytes) != cudaSuccess) {\n\t\t\tthrow std::bad_alloc {};\n\t\t}\n\t\treturn ret;\n\t}\n\n\tvoid do_deallocate(void* ptr, std::size_t bytes, std::size_t alignment) {//NOLINT(readability-convert-member-functions-to-static) Method is designed to be a non-static class member\n\t\t(void) bytes;\n\t\t(void) alignment;\n\n\t\tif(cudaFree(ptr) != cudaSuccess) {\n\t\t\tthrow std::bad_alloc {};\n\t\t}\n\t}\n};\n\n/// std::allocator\n/// stateless allocator\nstruct DeviceAllocator {\n\tusing mr_type = MemoryResource;\n\n\tDeviceAllocator()\t\t\t\t\t\t\t\t\t\t\t = default;\n\tDeviceAllocator(const DeviceAllocator& o) noexcept\t\t\t = default;\n\tDeviceAllocator(DeviceAllocator&& o) noexcept\t\t\t\t = default;\n\tDeviceAllocator& operator=(const DeviceAllocator& o) noexcept = default;\n\tDeviceAllocator& operator=(DeviceAllocator&& o) noexcept\t = default;\n\n\t[[nodiscard]] mr_type* resource() const {\n\t\treturn &DeviceMemoryResource::instance();\n\t}\n\n\tvoid* allocate(std::size_t bytes) {//NOLINT(readability-convert-member-functions-to-static) Method is designed to be a non-static class member\n\t\treturn resource()->allocate(bytes);\n\t}\n\tvoid deallocate(void* p, std::size_t bytes) {//NOLINT(readability-convert-member-functions-to-static) Method is designed to be a non-static class member\n\t\t(void) bytes;\n\n\t\tresource()->deallocate(p);\n\t}\n};\n\nstruct UnifiedAllocator {\n\tusing mr_type = MemoryResource;\n\n\tUnifiedAllocator()\t\t\t\t\t\t\t\t\t\t\t\t= default;\n\tUnifiedAllocator(const UnifiedAllocator& o) noexcept\t\t\t= default;\n\tUnifiedAllocator(UnifiedAllocator&& o) noexcept\t\t\t\t\t= default;\n\tUnifiedAllocator& operator=(const UnifiedAllocator& o) noexcept = default;\n\tUnifiedAllocator& operator=(UnifiedAllocator&& o) noexcept\t\t= default;\n\n\t[[nodiscard]] mr_type* resource() const {\n\t\treturn &UnifiedMemoryResource::instance();\n\t}\n\n\tvoid* allocate(std::size_t bytes) {//NOLINT(readability-convert-member-functions-to-static) Method is designed to be a non-static class member\n\t\treturn resource()->allocate(bytes);\n\t}\n\tvoid deallocate(void* p, std::size_t bytes) {//NOLINT(readability-convert-member-functions-to-static) Method is designed to be a non-static class member\n\t\t(void) bytes;\n\n\t\tresource()->deallocate(p);\n\t}\n};\n/// memory types: device only, pageable, pinned\n/// usage: static, intermediate, dynamic small, dynamic large, dynamic random\nstruct MonotonicAllocator : StackAllocator {\n\tusing base_t = StackAllocator;\n\n\tMonotonicAllocator(std::size_t texturealign_bytes, std::size_t total_mem_bytes)\n\t\t: StackAllocator {&DeviceMemoryResource::instance(), texturealign_bytes, total_mem_bytes} {\n\t\tstd::cout << std::string {\"monotonic allocator alignment (Bytes): \"} << texturealign_bytes << std::string {\"\\tsize (MB): \"} << static_cast(total_mem_bytes) / static_cast(1 << 20) << std::endl;//NOLINT(readability-magic-numbers) Unit conversion\n\t}\n\n\t~MonotonicAllocator() = default;\n\n\tMonotonicAllocator(const MonotonicAllocator& o) noexcept\t\t\t= default;\n\tMonotonicAllocator(MonotonicAllocator&& o) noexcept\t\t\t\t\t= default;\n\tMonotonicAllocator& operator=(const MonotonicAllocator& o) noexcept = default;\n\tMonotonicAllocator& operator=(MonotonicAllocator&& o) noexcept\t\t= default;\n\n\tauto borrow(std::size_t bytes) -> void* {//NOLINT(readability-convert-member-functions-to-static) Method is designed to be a non-static class member\n\t\treturn allocate(bytes);\n\t}\n\n\tvoid reset() {\n\t\tstd::size_t used_bytes\t= head - data;\n\t\tstd::size_t total_bytes = tail - data;\n\t\tif(used_bytes >= total_bytes * 3 / 4) {//NOLINT(readability-magic-numbers) Threshold values?\n\t\t\tbase_t::resource()->deallocate((void*) this->data, total_bytes);\n\t\t\tstd::size_t total_mem_bytes = total_bytes * 3 / 2;//NOLINT(readability-magic-numbers) Threshold values?\n\t\t\tthis->data\t\t\t\t\t= static_cast(base_t::resource()->allocate(total_mem_bytes));\n\t\t\tthis->head\t\t\t\t\t= this->data;\n\t\t\tthis->tail\t\t\t\t\t= this->data + total_mem_bytes;\n\t\t} else {\n\t\t\tthis->head = this->data;\n\t\t}\n\t}\n};\n\nstruct MonotonicVirtualAllocator : StackAllocator {\n\tusing base_t\t\t\t\t = StackAllocator;\n\t~MonotonicVirtualAllocator() = default;\n\n\tMonotonicVirtualAllocator(int devId, std::size_t texturealign_bytes, std::size_t total_mem_bytes)\n\t\t: StackAllocator {&UnifiedMemoryResource::instance(), texturealign_bytes, total_mem_bytes} {\n\t\t// checkCudaErrors(cudaMemAdvise(addr, total_mem_bytes,\n\t\t// cudaMemAdviseSetPreferredLocation, devId));\n\t\tstd::cout << std::string {\"monotonic virtual allocator alignment (Bytes): \"} << texturealign_bytes << std::string {\"\\tsize (MB): \"} << static_cast(total_mem_bytes) / static_cast(1 << 20) << std::endl;//NOLINT(readability-magic-numbers) Unit conversion\n\t}\n\n\tauto borrow(std::size_t bytes) -> void* {//NOLINT(readability-convert-member-functions-to-static) Method is designed to be a non-static class member\n\t\treturn allocate(bytes);\n\t}\n\n\tvoid reset() {\n\t\tstd::size_t used_bytes\t= head - data;\n\t\tstd::size_t total_bytes = tail - data;\n\t\tif(used_bytes >= total_bytes * 3 / 4) {//NOLINT(readability-magic-numbers) Threshold values?\n\t\t\tthis->resource()->deallocate((void*) this->data, total_bytes);\n\t\t\tstd::size_t total_mem_bytes = total_bytes * 3 / 2;//NOLINT(readability-magic-numbers) Threshold values?\n\t\t\tthis->data\t\t\t\t\t= static_cast(this->resource()->allocate(total_mem_bytes));\n\t\t\tthis->head\t\t\t\t\t= this->data;\n\t\t\tthis->tail\t\t\t\t\t= this->data + total_mem_bytes;\n\t\t} else {\n\t\t\tthis->head = this->data;\n\t\t}\n\t}\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnSystem/Cuda/Cuda.cu", "content": "#include \t ///<\tfor optimal kernel launching\n#include ///<\tfor evaluating kernel performance\n#include \n\n#include \n#include \n\n#include \"Cuda.h\"\n\nconstexpr size_t MEM_POOL_CTRL = 3;\n\nnamespace mn {\n\n//NOLINTBEGIN(cppcoreguidelines-pro-type-vararg) Cuda has no other way to print\nKernelConfig::KernelConfig(KernelFunc f, cudaFuncCache cache_config, bool is_wave)\n\t: attribs()\n\t, func(f)\n\t, cache_preference(cache_config)\n\t, wave_fashion(is_wave) {\n\tcudaFuncGetAttributes(&attribs, f);\n\tmax_occ_block_size = Cuda::eval_optimal_block_size(attribs, cache_preference);\n\tif(cache_config != cudaFuncCachePreferNone) {///< should be different from\n\t\t///< device cache preference\n\t\tcheck_cuda_errors(cudaFuncSetCacheConfig(f, cache_config));\n\t}\n}\n\nCuda::Cuda()\n\t: default_dev_id {0}\n\t, dev_num_using()\n\t, i_dev_id() {\n\tprintf(\"[Init -- Begin] Cuda\\n\");\n\t//< acquire devices\n\tdev_num_available\t = 0;\n\tcudaError_t error_id = cudaGetDeviceCount(&dev_num_available);\n\tif(error_id != cudaSuccess) {\n\t\tprintf(\"cudaGetDeviceCount returned %d\\n-> %s\\n\", static_cast(error_id), cudaGetErrorString(error_id));\n\t\tprintf(\"Result = FAIL\\n\");\n\t\tthrow std::runtime_error(\"Failure\");\n\t}\n\tif(dev_num_available == 0) {\n\t\tprintf(\n\t\t\t\"\\t[InitInfo -- DevNum] There are no available device(s) that \"\n\t\t\t\"support CUDA\\n\"\n\t\t);\n\t} else {\n\t\tprintf(\"\\t[InitInfo -- DevNum] Detected %d CUDA Capable device(s)\\n\", dev_num_available);\n\t}\n\tset_max_device();//<[TMP]\n\tprintf(\"\\t[InitInfo -- DevNum] Prepare to use %d device(s) in Multi-GPU test\\n\", dev_num_using);\n\n\tak_device_props.resize(dev_num_available);\n\tak_streams.resize(dev_num_available);\n\tak_events.resize(dev_num_available);\n\n\tfor(int i = 0; i < dev_num_available; i++) {\n\t\t// check_cuda_errors(cudaSetDevice(i));\n\t\tcheck_cuda_errors(cudaSetDevice(i));\n\t\t///< device properties\n\t\tcheck_cuda_errors(cudaGetDeviceProperties(&ak_device_props[i], i));\n\t\tconst auto& prop {ak_device_props[i]};\n\t\tprintf(\n\t\t\t\"\\t[InitInfo -- Dev Property] GPU device %d (%d-th group on \"\n\t\t\t\"board)\\n\\t\\tglobal memory: %llu bytes,\\n\\t\\tshared memory per \"\n\t\t\t\"block: %llu bytes,\\n\\t\\tregisters per SM: %d,\\n\\t\\tMulti-Processor \"\n\t\t\t\"count: %d,\\n\\t\\tSM compute capabilities: %d.%d.\\n\",\n\t\t\ti,\n\t\t\tprop.multiGpuBoardGroupID,\n\t\t\tstatic_cast(prop.totalGlobalMem),\n\t\t\tstatic_cast(prop.sharedMemPerBlock),\n\t\t\tprop.regsPerBlock,\n\t\t\tprop.multiProcessorCount,\n\t\t\tprop.major,\n\t\t\tprop.minor\n\t\t);\n\n\t\t///< streams\n\t\t// int leastPriority = 0;\n\t\t// int greatestPriority = leastPriority;\n\t\t// cudaDeviceGetStreamPriorityRange(&leastPriority, &greatestPriority);\n\t\t// cudaStreamCreateWithPriority(&compute_stream, cudaStreamDefault,\n\t\t// leastPriority); cudaStreamCreateWithPriority(&push_top_stream,\n\t\t// cudaStreamDefault, greatestPriority);\n\t\t// cudaStreamCreateWithPriority(&push_bottom_stream, cudaStreamDefault,\n\t\t// greatestPriority);\n\t\t// for (auto &stream : ak_streams[i])\n\t\tfor(int j = 0; j < static_cast(StreamIndex::TOTAL); ++j) {\n\t\t\tcheck_cuda_errors(cudaStreamCreate(&ak_streams[i][j]));\n\t\t}\n\t\tprintf(\"\\t[InitInfo -- stream] Create %lu streams for device %d\\n\", static_cast(ak_streams[i].extent), i);\n\n\t\t// for (auto &event : ak_events[i])\n\t\tfor(int j = 0; j < static_cast(EventIndex::TOTAL); ++j) {\n\t\t\tcheck_cuda_errors(cudaEventCreateWithFlags(\n\t\t\t\t&ak_events[i][j],// cudaEventDefault | cudaEventBlockingSync |\n\t\t\t\t// cudaEventInterprocess |\n\t\t\t\tcudaEventDisableTiming\n\t\t\t));\n\t\t}\n\n\t\t///< memory allocator\n\t\tstd::size_t free_byte, total_byte;\n\t\tcheck_cuda_errors(cudaMemGetInfo(&free_byte, &total_byte));\n\t\t///\n\t\tak_monotonic_allocators.emplace_back(std::make_unique(prop.textureAlignment,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t free_byte >> MEM_POOL_CTRL));///< preserve 1/4 space for intermediate\n\t\t///< computations\n\t\tcudaDeviceSynchronize();\n\t\tprintf(\n\t\t\t\"\\t[InitInfo -- memory] device %d\\n\\t\\tfree bytes/total bytes: \"\n\t\t\t\"%lu/%lu,\\n\\t\\tpre-allocated size: %lu bytes\\n\\n\",\n\t\t\ti,\n\t\t\tstatic_cast(free_byte),\n\t\t\tstatic_cast(total_byte),\n\t\t\tstatic_cast(free_byte >> MEM_POOL_CTRL)\n\t\t);\n\t}\n\n\t//< enable peer access\n\tfor(int i = 0; i < dev_num_available; i++) {\n\t\tfor(int j = 0; j < dev_num_available; j++) {\n\t\t\tif(i != j) {\n\t\t\t\testablish_peer_access(i, j);\n\t\t\t\tprintf(\"\\t[InitInfo -- Peer Access] Enable peer access from %d to %d\\n\", i, j);\n\t\t\t}\n\t\t}\n\t}\n\t//< init cuda context\n\tfor(int i = 0; i < dev_num_available; i++) {\n\t\tak_cu_dev_contexts.emplace_back(i);//< set device when construct\n\t}\n\n\tprintf(\"\\t[InitInfo -- Default Dev] Default context: %d\\n\", default_dev_id);\n\tcheck_cuda_errors(cudaSetDevice(default_dev_id));\n\tprintf(\"\\n[Init -- End] == Finished \\'Cuda\\' initialization\\n\\n\");\n\t// getchar();\n}\n\nCuda::~Cuda() {\n\t// cudaStreamDestroy(_kMemCopyStream);\n\tget_instance()->ak_device_props.clear();\n\tfor(auto& streams: get_instance()->ak_streams) {\n\t\t// for (auto &stream : streams)\n\t\tfor(int j = 0; j < static_cast(StreamIndex::TOTAL); ++j) {\n\t\t\tcheck_cuda_errors(cudaStreamDestroy(streams[j]));\n\t\t}\n\t}\n\tfor(auto& events: get_instance()->ak_events) {\n\t\t// for (auto &event : events)\n\t\tfor(int j = 0; j < static_cast(EventIndex::TOTAL); ++j) {\n\t\t\tcheck_cuda_errors(cudaEventDestroy(events[j]));\n\t\t}\n\t}\n\t//for (auto &monoAllocator : ak_monotonic_allocators){\n\t//for (int i = 0; i < get_instance()->ak_monotonic_allocators.size(); ++i){\n\t// get_instance()->ak_monotonic_allocators[i].~MonotonicAllocator();\n\t//}\n\t//}\n\tprintf(\" Finished \\'Cuda\\' termination\\n\");\n}\n\nint Cuda::general_grid_size(int& thread_num, int& block_size) const {\n\treturn (thread_num + block_size - 1) / block_size;\n}\n\nint Cuda::wave_grid_size(int& thread_num, int& block_size) const {\n\tauto blocksPerSM = (thread_num / block_size / get_instance()->ak_device_props[i_dev_id].multiProcessorCount) * get_instance()->ak_device_props[i_dev_id].multiProcessorCount;\n\treturn (blocksPerSM != 0) ? blocksPerSM : 1;\n}\n\n/// static methods\nint Cuda::eval_optimal_block_size(cudaFuncAttributes attribs, cudaFuncCache cache_preference, std::size_t smem_bytes) {\n\tauto* instance\t\t\t\t\t = get_instance();\n\tcudaOccDeviceProp prop\t\t\t = get_instance()->ak_device_props[instance->i_dev_id];///< cache preference\n\tcudaOccFuncAttributes occ_attribs = attribs;\n\tcudaOccDeviceState occ_cache;\n\tswitch(cache_preference) {\n\t\tcase cudaFuncCachePreferNone:\n\t\t\tocc_cache.cacheConfig = CACHE_PREFER_NONE;\n\t\t\tbreak;\n\t\tcase cudaFuncCachePreferShared:\n\t\t\tocc_cache.cacheConfig = CACHE_PREFER_SHARED;\n\t\t\tbreak;\n\t\tcase cudaFuncCachePreferL1:\n\t\t\tocc_cache.cacheConfig = CACHE_PREFER_L1;\n\t\t\tbreak;\n\t\tcase cudaFuncCachePreferEqual:\n\t\t\tocc_cache.cacheConfig = CACHE_PREFER_EQUAL;\n\t\t\tbreak;\n\t\tdefault:;///< should throw error\n\t}\n\tint minGridSize;\n\t//TODO: Make constant?\n\tint block_size = 32;//NOLINT(readability-magic-numbers) Is block size\n\tcudaOccMaxPotentialOccupancyBlockSize(&minGridSize, &block_size, &prop, &occ_attribs, &occ_cache, nullptr, smem_bytes);\n\treturn block_size;\n}\n\nExecutionPolicy Cuda::launch_config(std::string kernel_name, int thread_num, bool sync, std::size_t smem_size, cudaStream_t sid) const {\n\t(void) sid;\n\n\tauto* instance = get_instance();\n\tif(instance->k_func_table.find(kernel_name) == instance->k_func_table.end()) {\n\t\t//TODO: Make constant?\n\t\tint bs = 256;//NOLINT(readability-magic-numbers) Is block size\n\t\tprintf(\"Warning: Kernel function %s not registered! Use 256 setting!\\n\", kernel_name.data());\n\t\treturn {general_grid_size(thread_num, bs), bs, smem_size, sync};\n\t}\n\tauto& config = instance->k_func_table[kernel_name.data()];\n\tint bs\t\t = config.max_occ_block_size;\n\tif(smem_size > 0) {\n\t\tbs = eval_optimal_block_size(config.attribs, config.cache_preference, smem_size);\n\t}\n\t// printf(\"configurating for kernel[%s] blocksize: %d\\n\", kernel_name.c_str(),\n\t// bs);\n\tif(config.wave_fashion) {\n\t\treturn {wave_grid_size(thread_num, bs), bs, smem_size, sync};\n\t}\n\treturn {general_grid_size(thread_num, bs), bs, smem_size, sync};\n}\n\nvoid Cuda::register_kernel(std::string tag, KernelFunc f, cudaFuncCache cache_config, bool wave_fashion) {\n\tauto* instance = get_instance();\n\tinstance->k_func_table.emplace(tag, KernelConfig(f, cache_config, wave_fashion));\n\tprintf(\"Kernel[%s](%s) block size configuration: %d\\n\", tag.data(), wave_fashion ? \"wave\" : \"general\", instance->k_func_table[tag.data()].max_occ_block_size);\n}\nconst KernelConfig& Cuda::find_kernel(std::string tag) {\n\tauto* instance = get_instance();\n\treturn instance->k_func_table[tag.data()];\n}\n\n//NOLINTEND(cppcoreguidelines-pro-type-vararg) Cuda has no other way to print\n\n}// namespace mn\n" }, { "path": "Library/MnSystem/Cuda/Cuda.h", "content": "#ifndef SYSTEM_CUDA_H\n#define SYSTEM_CUDA_H\n\n#include \n//#include \n#include \n\n#include \n\n#include \"Allocators.cuh\"\n#include \"ExecutionPolicy.h\"\n#include \"HostUtils.hpp\"\n#include \"MnBase/Math/Vec.h\"\n#include \"MnBase/Meta/AllocMeta.cuh\"\n#include \"MnBase/Object/Function.h\"\n#include \"MnBase/Singleton.h\"\n\nnamespace mn {\n\nusing KernelFunc = const void*;\n\nstruct KernelConfig {///< static kernel attrib, could contain run-time debugger\n\t///< setting(error checking/ time recording etc...)\n\tKernelFunc func;\n\tcudaFuncAttributes attribs;\n\tcudaFuncCache cache_preference;\n\tbool wave_fashion;\t ///< general fashion or loop fashion\n\tint max_occ_block_size;///< condition: use no shared memory\n\texplicit KernelConfig(KernelFunc f = nullptr, cudaFuncCache cache_config = cudaFuncCachePreferNone, bool is_wave = false);\n};\n\nclass Cuda : public ManagedSingleton {\n public:\n\t/// kernel launching\n\tenum class StreamIndex {\n\t\tCOMPUTE = 0,\n\t\tH2DCOPY,\n\t\tD2HCOPY,\n\t\tD2DCOPY,\n\t\tSPARE,\n\t\tTOTAL = 32\n\t};\n\n\tenum class EventIndex {\n\t\tCOMPUTE = 0,\n\t\tH2DCOPY,\n\t\tD2HCOPY,\n\t\tD2DCOPY,\n\t\tSPARE,\n\t\tTOTAL = 32\n\t};\n\n\tstruct CudaContext {\n\t private:\n\t\tint dev_id;\n\n\t\tauto monotonicAllocator() -> MonotonicAllocator& {\n\t\t\t// setContext();\n\t\t\treturn *Cuda::get_instance()->ak_monotonic_allocators[dev_id];\n\t\t}\n\n\t public:\n\t\texplicit CudaContext(int dev_id = -1)\n\t\t\t: dev_id {dev_id} {\n\t\t\tif(dev_id != -1) {\n\t\t\t\tprintf(\"\\t[Init] CudaContext %d\\n\", dev_id);\n\t\t\t\tcheck_cuda_errors(cudaSetDevice(dev_id));\n\t\t\t}\n\t\t}\n\n\t\t//< context & prop\n\t\tvoid set_context() {\n\t\t\tcheck_cuda_errors(cudaSetDevice(dev_id));\n\t\t}\n\n\t\tauto get_dev_id() const noexcept {\n\t\t\treturn dev_id;\n\t\t}\n\n\t\tauto get_context_info() noexcept {\n\t\t\treturn dev_id;\n\t\t}\n\n\t\tconst auto& get_dev_prop() const noexcept {\n\t\t\treturn Cuda::get_instance()->ak_device_props[dev_id];\n\t\t}\n\n\t\t/// stream & event\n\t\t// stream\n\t\ttemplate\n\t\tauto stream() const -> cudaStream_t {\n\t\t\treturn Cuda::get_instance()->ak_streams[dev_id][static_cast(sid)];\n\t\t}\n\n\t\tauto stream(unsigned sid) const -> cudaStream_t {\n\t\t\treturn Cuda::get_instance()->ak_streams[dev_id][sid];\n\t\t}\n\n\t\tauto stream_compute() const -> cudaStream_t {\n\t\t\treturn Cuda::get_instance()->ak_streams[dev_id][static_cast(StreamIndex::COMPUTE)];\n\t\t}\n\n\t\tauto stream_spare(unsigned sid = 0) const -> cudaStream_t {\n\t\t\treturn Cuda::get_instance()->ak_streams[dev_id][static_cast(StreamIndex::SPARE) + sid];\n\t\t}\n\n\t\tvoid syncCompute() const {\n\t\t\tcheck_cuda_errors(cudaStreamSynchronize(Cuda::get_instance()->ak_streams[dev_id][static_cast(StreamIndex::COMPUTE)]));\n\t\t}\n\n\t\ttemplate\n\t\tvoid syncStream() const {\n\t\t\tcheck_cuda_errors(cudaStreamSynchronize(Cuda::get_instance()->ak_streams[dev_id][static_cast(sid)]));\n\t\t}\n\n\t\tvoid syncStream(unsigned sid) const {\n\t\t\tcheck_cuda_errors(cudaStreamSynchronize(Cuda::get_instance()->ak_streams[dev_id][sid]));\n\t\t}\n\n\t\tvoid syncStreamSpare(unsigned sid = 0) const {\n\t\t\tcheck_cuda_errors(cudaStreamSynchronize(Cuda::get_instance()->ak_streams[dev_id][static_cast(StreamIndex::SPARE) + sid]));\n\t\t}\n\n\t\t// event\n\t\tauto event_compute() const -> cudaEvent_t {\n\t\t\treturn Cuda::get_instance()->ak_events[dev_id][static_cast(EventIndex::COMPUTE)];\n\t\t}\n\n\t\tauto event_spare(unsigned eid = 0) const -> cudaEvent_t {\n\t\t\treturn Cuda::get_instance()->ak_events[dev_id][static_cast(EventIndex::SPARE) + eid];\n\t\t}\n\n\t\tauto compute_event_record() {\n\t\t\tcheck_cuda_errors(cudaEventRecord(event_compute(), stream_compute()));\n\t\t}\n\n\t\tauto spare_event_record(unsigned id = 0) {\n\t\t\tcheck_cuda_errors(cudaEventRecord(event_spare(id), stream_spare(id)));\n\t\t}\n\n\t\tvoid computeStreamWaitForEvent(cudaEvent_t event) {\n\t\t\tcheck_cuda_errors(cudaStreamWaitEvent(stream_compute(), event, 0));\n\t\t}\n\n\t\tvoid spareStreamWaitForEvent(unsigned sid, cudaEvent_t event) {\n\t\t\tcheck_cuda_errors(cudaStreamWaitEvent(stream_spare(sid), event, 0));\n\t\t}\n\n\t\t/// kernel launch\n\t\t///< 1. compute stream\n\t\ttemplate\n\t\tvoid compute_launch(\n\t\t\tLaunchConfig&& lc,\n\t\t\tFunc&& f,\n\t\t\tArguments... args\n\t\t) {///< launch on the current device\n\t\t\tstatic_assert(!std::disjunction...>::value, \"Cannot pass values to Cuda kernels by reference\");\n\t\t\t/// compiler will handle type conversions\n\t\t\tif(lc.dg.x && lc.dg.y && lc.dg.z && lc.db.x && lc.db.y && lc.db.z) {\n\t\t\t\tstd::forward(f)<<()>>>(args...);\n\t\t\t\tcudaError_t error = cudaGetLastError();\n\t\t\t\tif(error != cudaSuccess) {\n\t\t\t\t\tprintf(\"[Dev %d] Kernel launch failure on [COMPUTE stream] %s\\n\", dev_id, cudaGetErrorString(error));\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\n\t\ttemplate\n\t\tvoid compute_launch(\n\t\t\tLaunchConfig&& lc,\n\t\t\tvoid (*f)(Arguments...),\n\t\t\tArguments... args\n\t\t) {///< launch on the current device\n\t\t\tstatic_assert(!std::disjunction...>::value, \"Cannot pass values to Cuda kernels by reference\");\n\t\t\t/// compiler will handle type conversions\n\t\t\tif(lc.dg.x && lc.dg.y && lc.dg.z && lc.db.x && lc.db.y && lc.db.z) {\n\t\t\t\tf<<()>>>(args...);\n\t\t\t\tcudaError_t error = cudaGetLastError();\n\t\t\t\tif(error != cudaSuccess) {\n\t\t\t\t\tprintf(\"[Dev %d] Kernel launch failure on [COMPUTE stream] %s\\n\", dev_id, cudaGetErrorString(error));\n\t\t\t\t}\n\t\t\t\t// if(error!= cudaSuccess) getchar();\n\t\t\t}\n\t\t}\n\n\t\ttemplate\n\t\tvoid spare_launch(\n\t\t\tunsigned sid,\n\t\t\tLaunchConfig&& lc,\n\t\t\tFunc&& f,\n\t\t\tArguments... args\n\t\t) {///< launch on the current device\n\t\t\tstatic_assert(!std::disjunction...>::value, \"Cannot pass values to Cuda kernels by reference\");\n\t\t\t/// compiler will handle type conversions\n\t\t\tif(lc.dg.x && lc.dg.y && lc.dg.z && lc.db.x && lc.db.y && lc.db.z) {\n\t\t\t\tstd::forward(f)<<>>(std::forward(args)...);\n\t\t\t\tcudaError_t error = cudaGetLastError();\n\t\t\t\tif(error != cudaSuccess) {\n\t\t\t\t\tprintf(\"[Dev %d] Kernel launch failure on [COMPUTE stream] %s\\n\", dev_id, cudaGetErrorString(error));\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\n\t\ttemplate\n\t\tvoid spare_launch(\n\t\t\tunsigned sid,\n\t\t\tLaunchConfig&& lc,\n\t\t\tvoid (*f)(Arguments...),\n\t\t\tArguments... args\n\t\t) {///< launch on the current device\n\t\t\tstatic_assert(!std::disjunction...>::value, \"Cannot pass values to Cuda kernels by reference\");\n\t\t\t/// compiler will handle type conversions\n\t\t\tif(lc.dg.x && lc.dg.y && lc.dg.z && lc.db.x && lc.db.y && lc.db.z) {\n\t\t\t\tf<<>>(std::forward(args)...);\n\t\t\t\tcudaError_t error = cudaGetLastError();\n\t\t\t\tif(error != cudaSuccess) {\n\t\t\t\t\tprintf(\"[Dev %d] Kernel launch failure on [COMPUTE stream] %s\\n\", dev_id, cudaGetErrorString(error));\n\t\t\t\t}\n\t\t\t\t// if(error!= cudaSuccess) getchar();\n\t\t\t}\n\t\t}\n\n\t\t/// 2. general stream\n\t\t// template \n\t\t// void general_launch(LaunchConfig&& lc, Func&& f, Arguments... args) {\n\t\t// std::forward(f) <<() >>>\n\t\t// (std::forward(args)...); cudaError_t error =\n\t\t// cudaGetLastError(); if (error != cudaSuccess) printf(\"[Dev %d] Kernel\n\t\t// launch failure on [stream %lu] %s\\n\", dev_id, (unsigned long)sid,\n\t\t// cudaGetErrorString(error));\n\t\t// }\n\t\ttemplate\n\t\tvoid general_launch(\n\t\t\tLaunchConfig&& lc,\n\t\t\tvoid (*f)(Arguments...),\n\t\t\tArguments... args\n\t\t) {///< launch on the current device\n\t\t\tstatic_assert(!std::disjunction...>::value, \"Cannot pass values to Cuda kernels by reference\");\n\t\t\tif(lc.dg.x && lc.dg.y && lc.dg.z && lc.db.x && lc.db.y && lc.db.z) {\n\t\t\t\tf<<()>>>(std::forward(args)...);\n\t\t\t\tcudaError_t error = cudaGetLastError();\n\t\t\t\tif(error != cudaSuccess) {\n\t\t\t\t\tprintf(\"[Dev %d] Kernel launch failure on [stream %lu] %s\\n\", dev_id, (unsigned long) sid, cudaGetErrorString(error));\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\n\t\t///< 3. pre-allocated memory\n\t\tauto borrow(std::size_t bytes) -> void* {\n\t\t\treturn monotonicAllocator().borrow(bytes);\n\t\t}\n\n\t\tvoid reset_mem() {\n\t\t\tmonotonicAllocator().reset();\n\t\t}\n\n\t\t///< 4. cuda memset\n\n\t\ttemplate\n\t\tvoid memset(StreamIndex sid, const Integer size, Attrib addr, Type value) {\n\t\t\t// setContext();\n\t\t\tcheck_cuda_errors(cudaMemsetAsync(addr, value, sizeof(Type) * size, stream((unsigned) sid)));\n\t\t}\n\t};//< [end] struct CudaContext\n\n private:\n\tint dev_num_using;\n\tint dev_num_available;\n\n\tint default_dev_id;\n\tstd::vector ak_cu_dev_contexts;\n\n\tstd::vector ak_device_props;\n\tstd::vector> ak_streams;///< 16 is enough for most needs\n\tstd::vector> ak_events;\n\tstd::vector> ak_monotonic_allocators;///< an allocator is a handle to a heap\n\n\tstd::unordered_map k_func_table;\n\n\tint i_dev_id;///< need changing\n\n public:\n\tCuda();\n\t~Cuda();\n\n\tstatic void register_kernel(std::string tag, KernelFunc f, cudaFuncCache cache_config = cudaFuncCachePreferL1, bool wave_fashion = true);\n\tstatic const KernelConfig& find_kernel(std::string tag);\n\n\tint general_grid_size(int& thread_num, int& block_size) const;\n\tint wave_grid_size(int& thread_num, int& block_size) const;\n\tstatic int eval_optimal_block_size(cudaFuncAttributes attribs, cudaFuncCache cache_preference, size_t smem_bytes = 0);\n\tExecutionPolicy launch_config(std::string kernel_name, int thread_num, bool sync = false, size_t smem_size = 0, cudaStream_t sid = cudaStreamDefault) const;\n\n\tauto establish_peer_access(int devA, int devB) {\n\t\tcheck_cuda_errors(cudaSetDevice(devA));\n\t\tint canAccessPeer = 0;\n\t\tcheck_cuda_errors(cudaDeviceCanAccessPeer(&canAccessPeer, devA, devB));\n\t\tif(canAccessPeer) {\n\t\t\tcheck_cuda_errors(cudaDeviceEnablePeerAccess(devB, 0));\n\t\t\t// cudaSetDevice(i_dev_id);\n\t\t\treturn true;\n\t\t}\n\t\t// cudaSetDevice(i_dev_id);\n\t\treturn false;\n\t}\n\n\t//< dev_num info\n\tauto dev_using_count() noexcept {\n\t\treturn dev_num_using;\n\t}\n\tauto dev_available_count() noexcept {\n\t\treturn dev_num_available;\n\t}\n\n\tvoid set_max_device() noexcept {\n\t\tdev_num_using = dev_num_available;\n\t}\n\n\t//< context ref\n\tint get_default_dev_id() noexcept {\n\t\treturn default_dev_id;\n\t}\n\n\tstatic auto get_device_count() noexcept -> int {\n\t\treturn get_instance()->dev_num_available;\n\t}\n\tstatic auto ref_cuda_context(int dev_id) noexcept -> CudaContext& {\n\t\treturn get_instance()->ak_cu_dev_contexts[dev_id];\n\t}\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnSystem/Cuda/DeviceUtils.cu", "content": "#include \"DeviceUtils.cuh\"\n\nnamespace mn {\n\ntemplate\n__device__ int retrieve_block_local_offset(int level, uint64_t block_offset) {///< the level number starts from 0\n\treturn (block_offset >> (NumPageBits + level * 3)) & 7;\n}\n\n}// namespace mn\n" }, { "path": "Library/MnSystem/Cuda/DeviceUtils.cuh", "content": "#ifndef DEVICE_UTILS_CUH\n#define DEVICE_UTILS_CUH\n\n#include \n#include \n#include \n\nnamespace mn {\n\nnamespace cg = cooperative_groups;\n\n__forceinline__ __device__ double unsigned_longlong_as_double(unsigned long long val) {\n\tconst long long val_as_ll = *static_cast(static_cast(&val));\n\treturn __longlong_as_double(val_as_ll);\n}\n\n__forceinline__ __device__ unsigned long long double_as_unsigned_longlong(double val) {\n\tconst long long val_as_ll = __double_as_longlong(val);\n\treturn *static_cast(static_cast(&val_as_ll));\n}\n\n__forceinline__ __device__ int clzull(unsigned long long val) {\n\tconst long long val_as_ll = *static_cast(static_cast(&val));\n\treturn __clzll(val_as_ll);\n}\n\ntemplate\n__forceinline__ __device__ bool atomic_min(T* address, T val);\n\ntemplate\n__forceinline__ __device__ bool atomic_max(T* address, T val);\n\ntemplate\n__forceinline__ __device__ T atomic_add_float(T* address, T val);\n\ntemplate<>\n__forceinline__ __device__ float atomic_add_float(float* address, float val) {\n\tint* address_as_i = static_cast(static_cast(address));\n\tint old\t\t\t = *address_as_i;\n\tint assumed;\n\tdo {\n\t\tassumed = old;\n\t\told\t\t= atomicCAS(address_as_i, assumed, __float_as_int(val + __int_as_float(assumed)));\n\t} while(assumed != old);\n\treturn __int_as_float(old);\n}\ntemplate<>\n__forceinline__ __device__ double atomic_add_float(double* address, double val) {\n\tunsigned long long* address_as_ull = static_cast(static_cast(address));\n\tunsigned long long old\t\t\t = *address_as_ull;\n\tunsigned long long assumed;\n\tdo {\n\t\tassumed = old;\n\t\told\t\t= atomicCAS(address_as_ull, assumed, double_as_unsigned_longlong(val + unsigned_longlong_as_double(assumed)));\n\t} while(assumed != old);\n\treturn unsigned_longlong_as_double(old);\n}\n\ntemplate<>\n__forceinline__ __device__ bool atomic_min(float* address, float val) {\n\tint* address_as_i = static_cast(static_cast(address));\n\tint old\t\t\t = *address_as_i;\n\tint assumed;\n\tif(*address <= val) {\n\t\treturn false;\n\t}\n\tdo {\n\t\tassumed = old;\n\t\told\t\t= ::atomicCAS(address_as_i, assumed, __float_as_int(::fminf(val, __int_as_float(assumed))));\n\t} while(assumed != old);\n\treturn true;\n}\n\ntemplate<>\n__forceinline__ __device__ bool atomic_max(float* address, float val) {\n\tint* address_as_i = static_cast(static_cast(address));\n\tint old\t\t\t = *address_as_i;\n\tint assumed;\n\tif(*address >= val) {\n\t\treturn false;\n\t}\n\tdo {\n\t\tassumed = old;\n\t\told\t\t= ::atomicCAS(address_as_i, assumed, __float_as_int(::fmaxf(val, __int_as_float(assumed))));\n\t} while(assumed != old);\n\treturn true;\n}\n\ntemplate<>\n__forceinline__ __device__ bool atomic_min(double* address, double val) {\n#ifdef _WIN32\n\tuint64_t* address_as_ull = static_cast(static_cast(address));\n\tuint64_t old\t\t\t = *address_as_ull;\n\tuint64_t assumed;\n#else\n\tunsigned long long* address_as_ull = static_cast(static_cast(address));\n\tunsigned long long old\t\t\t = *address_as_ull;\n\tunsigned long long assumed;\n#endif// _WIN32\n\tif(*address <= val) {\n\t\treturn false;\n\t}\n\tdo {\n\t\tassumed = old;\n\t\told\t\t= ::atomicCAS(address_as_ull, assumed, double_as_unsigned_longlong(::fmin(val, unsigned_longlong_as_double(assumed))));\n\t} while(assumed != old);\n\treturn true;\n}\n\ntemplate<>\n__forceinline__ __device__ bool atomic_max(double* address, double val) {\n#ifdef _WIN32\n\tuint64_t* address_as_ull = static_cast(static_cast(address));\n\tuint64_t old\t\t\t = *address_as_ull;\n\tuint64_t assumed;\n#else\n\tunsigned long long* address_as_ull = static_cast(static_cast(address));\n\tunsigned long long old\t\t\t = *address_as_ull;\n\tunsigned long long assumed;\n#endif// _WIN32\n\tif(*address >= val) {\n\t\treturn false;\n\t}\n\tdo {\n\t\tassumed = old;\n\t\told\t\t= ::atomicCAS(address_as_ull, assumed, double_as_unsigned_longlong(::fmax(val, unsigned_longlong_as_double(assumed))));\n\t} while(assumed != old);\n\treturn true;\n}\n\n__device__ uint64_t packed_add(const uint64_t* masks, const uint64_t i, const uint64_t j);\n\ntemplate\n__device__ uint64_t packed_add_father_neighbor(const uint64_t* masks, const uint64_t child_offset, const int father_level, const uint64_t father_neighbor_offset);\n\ntemplate\n__device__ int retrieve_block_local_offset(int level, uint64_t block_offset);\n\n__forceinline__ __device__ uint64_t bit_spread_cuda(const uint64_t mask, int data) {\n\tuint64_t rmask\t= __brevll(mask);\n\tuint64_t result = 0;\n\tunsigned char lz;\n\tunsigned char offset = clzull(rmask);\n\twhile(rmask != 0) {\n\t\tlz\t = clzull(rmask) + 1;\n\t\tresult = result << lz | (data & 1);\n\t\tdata >>= 1, rmask <<= lz;\n\t}\n\tresult = __brevll(result) >> clzull(mask);\n\treturn result;\n}\n\n//NOLINTBEGIN(cppcoreguidelines-pro-type-union-access) Allowed in CUDA\n__forceinline__ __device__ int bit_pack_cuda(const uint64_t mask, uint64_t data) {\n\tunion {\n\t\tuint64_t slresult;\n\t\tuint64_t ulresult;\n\t} un\t\t= {};//FIXME:Why this union? (Both members have the same type)\n\tint count\t= 0;\n\tun.ulresult = 0;\n\n\tuint64_t rmask = __brevll(mask);\n\tunsigned char lz;\n\n\twhile(rmask != 0) {\n\t\tlz = clzull(rmask);\n\t\tdata >>= lz;\n\t\tun.ulresult <<= 1;\n\t\tcount++;\n\t\tun.ulresult |= (data & 1);\n\t\tdata >>= 1;\n\t\trmask <<= lz + 1;\n\t}\n\t//NOLINTNEXTLINE(readability-magic-numbers) Define as constant?\n\tun.ulresult <<= 64 - count;// 64 means 64 bits ... maybe not use a constant 64 ...\n\tun.ulresult = __brevll(un.ulresult);\n\treturn static_cast(un.slresult);\n}\n//NOLINTEND(cppcoreguidelines-pro-type-union-access)\n\ntemplate\n__forceinline__ __device__ T atomic_agg_inc(T* p) {\n\t//Create group for all threads in this warp\n\tcg::coalesced_group g = cg::coalesced_threads();\n\n\t//First thread increases size\n\tT prev;\n\tif(g.thread_rank() == 0) {\n\t\tprev = atomicAdd(p, g.size());\n\t}\n\n\t//All threads fetch the value from the first thread and add their rank as offset\n\tprev = g.thread_rank() + g.shfl(prev, 0);\n\treturn prev;\n}\n\n}// namespace mn\n\n#endif\n" }, { "path": "Library/MnSystem/Cuda/ExecutionPolicy.h", "content": "#ifndef CUDA_EXECUTION_POLICY_H\n#define CUDA_EXECUTION_POLICY_H\n#include \n\n#include \n\nnamespace mn {\n\nstruct LaunchConfig {\n\tdim3 dg {};\n\tdim3 db {};\n\tstd::size_t shmem {0};\n\tcudaStream_t sid {cudaStreamDefault};\n\n\ttemplate\n\tLaunchConfig(IndexType0 gs, IndexType1 bs)\n\t\t: dg {static_cast(gs)}\n\t\t, db {static_cast(bs)}\n\t\t, shmem {0}\n\t\t, sid {cudaStreamDefault} {}\n\n\ttemplate\n\tLaunchConfig(IndexType0 gs, IndexType1 bs, IndexType2 mem)\n\t\t: dg {static_cast(gs)}\n\t\t, db {static_cast(bs)}\n\t\t, shmem {static_cast(mem)}\n\t\t, sid {cudaStreamDefault} {}\n\n\ttemplate\n\tLaunchConfig(IndexType0 gs, IndexType1 bs, IndexType2 mem, cudaStream_t stream)\n\t\t: dg {static_cast(gs)}\n\t\t, db {static_cast(bs)}\n\t\t, shmem {static_cast(mem)}\n\t\t, sid {stream} {}\n};\n\nstruct LaunchInput {///< could contain more information on operation (error checking/ time recording/ etc...)\n private:\n\tconst std::string kernel_name;\n\tconst int num_threads;\n\tconst std::size_t shared_mem_bytes;\n\n public:\n\tLaunchInput() = delete;\n\tLaunchInput(std::string kernel, int task_num, std::size_t shared_mem_bytes = 0)\n\t\t: kernel_name(kernel)\n\t\t, num_threads(task_num)\n\t\t, shared_mem_bytes(shared_mem_bytes) {}\n\n\tconst std::string& name() {\n\t\treturn kernel_name;\n\t}\n\n\tconst int& threads() {\n\t\treturn num_threads;\n\t}\n\n\tconst std::size_t& mem_bytes() {\n\t\treturn shared_mem_bytes;\n\t}\n};\n\n/// kernel launching configuration\nstruct ExecutionPolicy {\n private:\n\tint grid_size {0};\n\tint block_size {0};\n\tstd::size_t shared_mem_bytes {0};\n\tbool sync {false};\n\n public:\n\tExecutionPolicy() {}\n\tExecutionPolicy(int gs, int bs, std::size_t memsize, bool s)\n\t\t: grid_size(gs)\n\t\t, block_size(bs)\n\t\t, shared_mem_bytes(memsize)\n\t\t, sync(s) {}\n\n\tint get_grid_size() const {\n\t\treturn grid_size;\n\t}\n\n\tint get_block_size() const {\n\t\treturn block_size;\n\t}\n\n\tstd::size_t get_shared_mem_bytes() const {\n\t\treturn shared_mem_bytes;\n\t}\n\n\tbool need_sync() const {\n\t\treturn sync;\n\t}\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnSystem/Cuda/HostUtils.hpp", "content": "#ifndef HOST_UTILS_HPP\n#define HOST_UTILS_HPP\n\n#include \n#include \n\n#include \n\nnamespace mn {\n\n#define check_thrust_errors(func) \\\n\ttry { \\\n\t\tfunc; \\\n\t} catch(thrust::system_error & e) { \\\n\t\tstd::cout << std::string(__FILE__) << \":\" << __LINE__ << \" \" << e.what() << std::endl; \\\n\t}\n\ninline static const char* cuda_get_error_enum(cudaError_t error) {\n\treturn cudaGetErrorName(error);\n}\n\n#ifdef __DRIVER_TYPES_H__\n#\tifndef DEVICE_RESET\n#\t\tdefine DEVICE_RESET cudaDeviceReset();\n#\tendif\n#else\n#\tifndef DEVICE_RESET\n#\t\tdefine DEVICE_RESET\n#\tendif\n#endif\n\ntemplate\nvoid check(T result, char const* const func, const char* const file, int const line) {\n\tif(result) {\n\t\tfprintf(stderr, \"CUDA error at %s:%d code=%d(%s) \\\"%s\\\" \\n\", file, line, static_cast(result), cuda_get_error_enum(result), func);\n\t\tDEVICE_RESET\n\t\t// Make sure we call CUDA Device Reset before exiting\n\t\texit(EXIT_FAILURE);\n\t}\n}\n\n// This will output the proper CUDA error strings in the event\n// that a CUDA host call returns an error\n#define check_cuda_errors(val) check((val), #val, __FILE__, __LINE__)\n\n// This will output the proper error string when calling cudaGetLastError\n#define get_last_cuda_error(msg) get_last_cuda_error_impl(msg, __FILE__, __LINE__)\n\ninline void get_last_cuda_error_impl(const char* errorMessage, const char* file, const int line) {\n\tcudaError_t err = cudaGetLastError();\n\n\tif(cudaSuccess != err) {\n\t\tfprintf(\n\t\t\tstderr,\n\t\t\t\"%s(%i) : get_last_cuda_error() CUDA error :\"\n\t\t\t\" %s : (%d) %s.\\n\",\n\t\t\tfile,\n\t\t\tline,\n\t\t\terrorMessage,\n\t\t\tstatic_cast(err),\n\t\t\tcudaGetErrorString(err)\n\t\t);\n\t\tDEVICE_RESET\n\t\texit(EXIT_FAILURE);\n\t}\n}\n\ntemplate\n__inline__ __host__ T* get_raw_ptr(thrust::device_vector& V) {\n\treturn thrust::raw_pointer_cast(V.data());\n}\ntemplate\n__inline__ __host__ thrust::device_ptr get_device_ptr(thrust::device_vector& V) {\n\treturn thrust::device_ptr(thrust::raw_pointer_cast(V.data()));\n}\ntemplate\n__inline__ __host__ thrust::device_ptr get_device_ptr(T* V) {\n\treturn thrust::device_ptr(V);\n}\n\ninline void report_memory(std::string msg) {\n\tstd::size_t free_byte;\n\tstd::size_t total_byte;\n\tcudaError_t cuda_status = cudaMemGetInfo(&free_byte, &total_byte);\n\n\tif(cudaSuccess != cuda_status) {\n\t\tprintf(\"Error: cudaMemGetInfo fails, %s \\n\", cudaGetErrorString(cuda_status));\n\t\texit(1);\n\t}\n\n\tdouble free_db\t= (double) free_byte;\n\tdouble total_db = (double) total_byte;\n\tdouble used_db\t= total_db - free_db;\n\tprintf(\"GPU memory usage (%s): used = %f, free = %f MB, total = %f MB\\n\", msg.data(), used_db / 1024.0 / 1024.0, free_db / 1024.0 / 1024.0, total_db / 1024.0 / 1024.0);\n}\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnSystem/Cuda/KernelLauncher.cuh", "content": "#ifndef KERNEL_LAUNCHER_CUH\n#define KERNEL_LAUNCHER_CUH\n\n#include \"ExecutionPolicy.h\"\n#include \"MnUtility/Profiler/Performance/CudaTimer.cuh\"\n\nnamespace mn {\n\ntemplate\nvoid cuda_launch(LaunchConfig&& lc, Func&& f, Arguments... args) {///< launch on the current device\n\tstatic_assert(!std::disjunction...>::value, \"Cannot pass values to Cuda kernels by reference\");\n\t/// compiler will handle type conversions\n\tstd::forward(f)<<>>(std::forward(args)...);\n\tcudaError_t error = cudaGetLastError();\n\tif(error != cudaSuccess) {\n\t\tprintf(\"Kernel launch failure %s\\n\", cudaGetErrorString(error));\n\t}\n}\n\n/// backup\ntemplate\nvoid cuda_launch(LaunchConfig&& lc, void (*f)(Arguments...), Arguments... args) {///< launch on the current device\n\tstatic_assert(!std::disjunction...>::value, \"Cannot pass values to Cuda kernels by reference\");\n\t/// compiler will handle type conversions\n\tf<<>>(std::forward(args)...);\n\tcudaError_t error = cudaGetLastError();\n\tif(error != cudaSuccess) {\n\t\tprintf(\"Kernel launch failure %s\\n\", cudaGetErrorString(error));\n\t}\n}\n\n/// option: 1 error checking 2 execution time recording 3 synchronizing\ntemplate\nvoid debug_launch(int gs, int bs, void (*f)(Arguments...), Arguments... args) {\n\tstatic_assert(!std::disjunction...>::value, \"Cannot pass values to Cuda kernels by reference\");\n\tcudaError_t error;\n\tf<<>>(std::forward(args)...);\n\tcudaDeviceSynchronize();\n\terror = cudaGetLastError();\n\tif(error != cudaSuccess) {\n\t\tprintf(\"Kernel launch failure %s\\n\", cudaGetErrorString(error));\n\t}\n}\n\ntemplate\nvoid record_launch(std::string&& tag, int gs, int bs, std::size_t mem, void (*f)(Arguments...), Arguments... args) {\n\tstatic_assert(!std::disjunction...>::value, \"Cannot pass values to Cuda kernels by reference\");\n\tCudaTimer timer;\n\tif(!mem) {\n\t\ttimer.tick();\n\t\tf<<>>(std::forward(args)...);\n\t\ttimer.tock(tag);\n\t} else {\n\t\ttimer.tick();\n\t\tf<<>>(std::forward(args)...);\n\t\ttimer.tock(tag);\n\t}\n\tcudaError_t error = cudaGetLastError();\n\tif(error != cudaSuccess) {\n\t\tprintf(\"Kernel launch failure %s\\n\", cudaGetErrorString(error));\n\t}\n}\n\ntemplate\nvoid cleanLaunch(int gs, int bs, void (*f)(Arguments...), Arguments... args) {\n\tstatic_assert(!std::disjunction...>::value, \"Cannot pass values to Cuda kernels by reference\");\n\tf<<>>(args...);\n}\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnSystem/Cuda/MemoryUtils.cu", "content": "#include \"Cuda.h\"\n#include \"MemoryUtils.cuh\"\n\nnamespace mn {}// namespace mn" }, { "path": "Library/MnSystem/Cuda/MemoryUtils.cuh", "content": "#ifndef MEMORY_UTILS_CUH\n#define MEMORY_UTILS_CUH\n#include \"Allocators.cuh\"\n\nnamespace mn {}// namespace mn\n\n#endif" }, { "path": "Library/MnSystem/IO/IO.cpp", "content": "#include \"IO.h\"\n//#include \n//#include \n//#include \n\nnamespace mn {\n\n/*\nvoid f()\n{\n double foo = -0.0;\n double bar = 0.0;\n\n auto res = foo <=> bar;\n\n if (res < 0)\n std::cout << \"-0 is less than 0\";\n else if (res == 0)\n std::cout << \"-0 and 0 are equal\";\n else if (res > 0)\n std::cout << \"-0 is greater than 0\";\n}\n*/\n\n}// namespace mn" }, { "path": "Library/MnSystem/IO/IO.h", "content": "#ifndef IO_H\n#define IO_H\n#include \n\n#include \"MnBase/Concurrency/Concurrency.h\"\n#include \"MnBase/Singleton.h\"\n\nnamespace mn {\n\nstruct IO : Singleton {\n private:\n\tbool b_running;\n\tstd::mutex mut;\n\tstd::condition_variable cv;\n\tThreadsafeQueue> jobs;\n\tstd::thread th;\n\n\tvoid wait() {\n\t\tstd::unique_lock lk {mut};\n\t\tcv.wait(lk, [this]() {\n\t\t\treturn !this->b_running || !this->jobs.empty();\n\t\t});\n\t};\n\tvoid worker() {\n\t\twhile(b_running) {\n\t\t\twait();\n\t\t\tauto job = jobs.try_pop();\n\t\t\tif(job) {\n\t\t\t\t(*job)();\n\t\t\t}\n\t\t}\n\t}\n\n public:\n\tIO()\n\t\t: b_running {true} {\n\t\tth = std::thread([this]() {\n\t\t\tthis->worker();\n\t\t});\n\t}\n\n\t~IO() {\n\t\twhile(!jobs.empty()) {\n\t\t\tcv.notify_all();\n\t\t}\n\t\tb_running = false;\n\t\tth.join();\n\t}\n\n\t//TODO: Maybe implement\n\tIO(IO& other)\t\t\t = delete;\n\tIO(IO&& other)\t\t\t = delete;\n\tIO& operator=(IO& other) = delete;\n\tIO& operator=(IO&& other) = delete;\n\n\tstatic void flush() {\n\t\twhile(!instance().jobs.empty()) {\n\t\t\tinstance().cv.notify_all();\n\t\t}\n\t}\n\tstatic void insert_job(const std::function& job) {\n\t\tstd::unique_lock lk {instance().mut};\n\t\tinstance().jobs.push(job);\n\t\tlk.unlock();\n\t\tinstance().cv.notify_all();\n\t}\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnSystem/IO/ParticleIO.hpp", "content": "#ifndef __PARTICLE_IO_HPP_\n#define __PARTICLE_IO_HPP_\n#include \n\n#include \n#include \n#include \n\n#include \"MnBase/Math/Vec.h\"\n#include \"PoissonDisk/SampleGenerator.h\"\n\nnamespace mn {\n\ntemplate\nvoid write_partio(const std::string& filename, const std::vector>& data, const std::string& tag = std::string {\"position\"}) {\n\tPartio::ParticlesDataMutable* parts = Partio::create();\n\n\tPartio::ParticleAttribute attrib = parts->addAttribute(tag.c_str(), Partio::VECTOR, dim);\n\n\tparts->addParticles(data.size());\n\tfor(int idx = 0; idx < (int) data.size(); ++idx) {\n\t\tfloat* val = parts->dataWrite(attrib, idx);\n\t\tfor(int k = 0; k < dim; k++) {\n\t\t\tval[k] = data[idx][k];\n\t\t}\n\t}\n\tPartio::write(filename.c_str(), *parts);\n\tparts->release();\n}\n\n/// have issues\nauto read_sdf(const std::string& fn, float ppc, float dx, vec offset, vec lengths) {\n\tstd::vector> data;\n\tstd::string filename = std::string(AssetDirPath) + \"MpmParticles/\" + fn;\n\n\tfloat levelsetDx;\n\tSampleGenerator pd;\n\tstd::vector samples;\n\tvec mins;\n\tvec maxs;\n\tvec scales;\n\tvec maxns;\n\tpd.LoadSDF(filename, levelsetDx, mins[0], mins[1], mins[2], maxns[0], maxns[1], maxns[2]);\n\tmaxs\t\t= maxns.cast() * levelsetDx;\n\tscales\t\t= lengths / (maxs - mins);\n\tfloat scale = scales[0] < scales[1] ? scales[0] : scales[1];\n\tscale\t\t= scales[2] < scale ? scales[2] : scale;\n\n\tfloat samplePerLevelsetCell = ppc * levelsetDx / dx * scale;\n\n\tpd.GenerateUniformSamples(samplePerLevelsetCell, samples);\n\n\tfor(int i = 0, size = samples.size() / 3; i < size; i++) {\n\t\tvec p {samples[i * 3 + 0], samples[i * 3 + 1], samples[i * 3 + 2]};\n\t\tp = (p - mins) * scale + offset;\n\t\t// particle[0] = ((samples[i * 3 + 0]) + offset[0]);\n\t\t// particle[1] = ((samples[i * 3 + 1]) + offset[1]);\n\t\t// particle[2] = ((samples[i * 3 + 2]) + offset[2]);\n\t\tdata.push_back(std::array {p[0], p[1], p[2]});\n\t}\n\tprintf(\"[%f, %f, %f] - [%f, %f, %f], scale %f, parcount %d, lsdx %f, dx %f\\n\", mins[0], mins[1], mins[2], maxs[0], maxs[1], maxs[2], scale, (int) data.size(), levelsetDx, dx);\n\treturn data;\n}\n\nauto read_sdf(const std::string& fn, float ppc, float dx, int domainsize, vec offset, vec lengths) {\n\tstd::vector> data;\n\tstd::string filename = std::string(AssetDirPath) + \"MpmParticles/\" + fn;\n\n\tfloat levelsetDx;\n\tSampleGenerator pd;\n\tstd::vector samples;\n\tvec mins;\n\tvec maxs;\n\tvec scales;\n\tvec maxns;\n\tpd.LoadSDF(filename, levelsetDx, mins[0], mins[1], mins[2], maxns[0], maxns[1], maxns[2]);\n\tmaxs = maxns.cast() * levelsetDx;\n\n\tscales\t\t\t\t\t\t= maxns.cast() / domainsize;\n\tfloat scale\t\t\t\t\t= scales[0] < scales[1] ? scales[0] : scales[1];\n\tscale\t\t\t\t\t\t= scales[2] < scale ? scales[2] : scale;\n\tfloat samplePerLevelsetCell = ppc * scale;\n\n\tpd.GenerateUniformSamples(samplePerLevelsetCell, samples);\n\n\tscales = lengths / (maxs - mins) / maxns.cast();\n\tscale = scales[0] < scales[1] ? scales[0] : scales[1];\n\tscale = scales[2] < scale ? scales[2] : scale;\n\n\tfor(int i = 0, size = samples.size() / 3; i < size; i++) {\n\t\tvec p {samples[i * 3 + 0], samples[i * 3 + 1], samples[i * 3 + 2]};\n\t\tp = (p - mins) * scale + offset;\n\t\tdata.push_back(std::array {p[0], p[1], p[2]});\n\t}\n\tprintf(\"[%f, %f, %f] - [%f, %f, %f], scale %f, parcount %d, lsdx %f, dx %f\\n\", mins[0], mins[1], mins[2], maxs[0], maxs[1], maxs[2], scale, (int) data.size(), levelsetDx, dx);\n\treturn data;\n}\n\n}// namespace mn\n\n#endif" }, { "path": "Library/MnSystem/IO/PoissonDisk/PoissonDisk.h", "content": "#include \n#include \n#include \n#include \n\n#include \"cyPoint.h\"\n#include \"cySampleElim.h\"\n\nclass PoissonDisk {\n public:\n\tPoissonDisk();\n\t~PoissonDisk();\n\n\tvoid LoadSDF(std::string filename);\n\tvoid GenerateSamples(int samplesPerVol, std::vector& outputSamples, int inputScale = 5);\n\n protected:\n\tinline float fetchGrid(int i, int j, int k) {\n\t\treturn m_phiGrid[i + m_ni * (j + m_nj * k)];\n\t}\n\tinline float fetchGridTrilinear(float x, float y, float z) {\n\t\tfloat dx = x - floor(x);\n\t\tfloat dy = y - floor(y);\n\t\tfloat dz = z - floor(z);\n\n\t\tfloat c000 = fetchGrid(floor(x), floor(y), floor(z));\n\t\tfloat c001 = fetchGrid(floor(x), floor(y), ceil(z));\n\t\tfloat c010 = fetchGrid(floor(x), ceil(y), floor(z));\n\t\tfloat c011 = fetchGrid(floor(x), ceil(y), ceil(z));\n\t\tfloat c100 = fetchGrid(ceil(x), floor(y), floor(z));\n\t\tfloat c101 = fetchGrid(ceil(x), floor(y), ceil(z));\n\t\tfloat c110 = fetchGrid(ceil(x), ceil(y), floor(z));\n\t\tfloat c111 = fetchGrid(ceil(x), ceil(y), ceil(z));\n\n\t\tfloat c00 = c000 * (1 - dx) + c100 * dx;\n\t\tfloat c01 = c001 * (1 - dx) + c101 * dx;\n\t\tfloat c10 = c010 * (1 - dx) + c110 * dx;\n\t\tfloat c11 = c011 * (1 - dx) + c111 * dx;\n\n\t\tfloat c0 = c00 * (1 - dy) + c10 * dy;\n\t\tfloat c1 = c01 * (1 - dy) + c11 * dy;\n\n\t\treturn c0 * (1 - dz) + c1 * dz;\n\t}\n\n private:\n\tint m_ni, m_nj, m_nk;\n\tfloat m_dx;\n\tint m_padding;\n\tcyPoint3f m_minBox;\n\tstd::vector m_phiGrid;\n\tcy::WeightedSampleElimination m_wse;\n};\n\nPoissonDisk::PoissonDisk() {}\n\nPoissonDisk::~PoissonDisk() {}\n\nvoid PoissonDisk::LoadSDF(std::string filename) {\n\tstd::ifstream infile(filename);\n\tinfile >> m_ni >> m_nj >> m_nk;\n\tinfile >> m_minBox[0] >> m_minBox[1] >> m_minBox[2];\n\tinfile >> m_dx;\n\n\tstd::cout << \"load grid size \" << m_ni << \", \" << m_nj << \", \" << m_nk << std::endl;\n\n\tint gridSize = m_ni * m_nj * m_nk;\n\tm_phiGrid.resize(gridSize);\n\tfor(int i = 0; i < gridSize; ++i) {\n\t\tinfile >> m_phiGrid[i];\n\t}\n\tinfile.close();\n}\n\nvoid PoissonDisk::GenerateSamples(int samplesPerVol, std::vector& outputSamples, int inputScale) {\n\tint numSamples = m_phiGrid.size() * samplesPerVol;\n\n\tstd::cout << \"Generate input \" << numSamples * inputScale << \" samples...\";\n\tstd::vector inputPoints(numSamples * inputScale);\n\tfor(size_t i = 0; i < inputPoints.size(); i++) {\n\t\tinputPoints[i].x = (float) rand() / RAND_MAX * (m_ni - 1);\n\t\tinputPoints[i].y = (float) rand() / RAND_MAX * (m_nj - 1);\n\t\tinputPoints[i].z = (float) rand() / RAND_MAX * (m_nk - 1);\n\t}\n\tstd::cout << \"done\\n\";\n\n\tstd::cout << \"Eliminate samples...\";\n\tstd::vector tmpPoints;\n\ttmpPoints.resize(numSamples);\n\tm_wse.Eliminate(inputPoints.data(), inputPoints.size(), tmpPoints.data(), tmpPoints.size());\n\tstd::cout << \"done\\n\";\n\n\toutputSamples.clear();\n\tfor(int i = 0; i < (int) tmpPoints.size(); i++) {\n\t\tif(fetchGridTrilinear(tmpPoints[i].x, tmpPoints[i].y, tmpPoints[i].z) < 0) {\n\t\t\toutputSamples.push_back(tmpPoints[i].x);\n\t\t\toutputSamples.push_back(tmpPoints[i].y);\n\t\t\toutputSamples.push_back(tmpPoints[i].z);\n\t\t}\n\t}\n}\n" }, { "path": "Library/MnSystem/IO/PoissonDisk/SampleGenerator.h", "content": "#if 1\n#\tinclude \n\n#\tinclude \n#\tinclude \n#\tinclude \n#\tinclude \n#\tinclude \n\n#\tinclude \"cyPoint.h\"\n#\tinclude \"cySampleElim.h\"\n\nclass SampleGenerator {\n public:\n\tSampleGenerator();\n\t~SampleGenerator();\n\n\tvoid test();\n\tvoid LoadSDF(std::string filename, float& pDx, float& minx, float& miny, float& minz, int& ni, int& nj, int& nk);\n\tvoid GeneratePoissonSamples(float samplesPerVol, std::vector& outputSamples, int inputScale = 5);\n\n\tvoid GeneratePoissonSamples(int length, int width, int height, float scale, int outputSamplesNumber, std::vector& outputSamples, int inputScale = 5);\n\n\tint GenerateUniformSamples(float samplesPerVol, std::vector& outputSamples);\n\n protected:\n\tinline float fetchGrid(int i, int j, int k) {\n\t\treturn m_phiGrid[i + m_ni * (j + m_nj * k)];\n\t}\n\tinline float fetchGridTrilinear(float x, float y, float z) {\n\t\tfloat dx = x - floor(x);\n\t\tfloat dy = y - floor(y);\n\t\tfloat dz = z - floor(z);\n\n\t\tfloat c000 = fetchGrid((int) floor(x), (int) floor(y), (int) floor(z));\n\t\tfloat c001 = fetchGrid((int) floor(x), (int) floor(y), (int) ceil(z));\n\t\tfloat c010 = fetchGrid((int) floor(x), (int) ceil(y), (int) floor(z));\n\t\tfloat c011 = fetchGrid((int) floor(x), (int) ceil(y), (int) ceil(z));\n\t\tfloat c100 = fetchGrid((int) ceil(x), (int) floor(y), (int) floor(z));\n\t\tfloat c101 = fetchGrid((int) ceil(x), (int) floor(y), (int) ceil(z));\n\t\tfloat c110 = fetchGrid((int) ceil(x), (int) ceil(y), (int) floor(z));\n\t\tfloat c111 = fetchGrid((int) ceil(x), (int) ceil(y), (int) ceil(z));\n\n\t\tfloat c00 = c000 * (1 - dx) + c100 * dx;\n\t\tfloat c01 = c001 * (1 - dx) + c101 * dx;\n\t\tfloat c10 = c010 * (1 - dx) + c110 * dx;\n\t\tfloat c11 = c011 * (1 - dx) + c111 * dx;\n\n\t\tfloat c0 = c00 * (1 - dy) + c10 * dy;\n\t\tfloat c1 = c01 * (1 - dy) + c11 * dy;\n\n\t\treturn c0 * (1 - dz) + c1 * dz;\n\t}\n\n private:\n\tint m_ni, m_nj, m_nk;\n\tfloat m_dx;\n\tint m_padding;\n\tcyPoint3f m_minBox;\n\tstd::vector m_phiGrid;\n\tcy::WeightedSampleElimination m_wse;\n};\n\nSampleGenerator::SampleGenerator() {}\n\nSampleGenerator::~SampleGenerator() {}\n\nvoid SampleGenerator::LoadSDF(std::string filename, float& pDx, float& minx, float& miny, float& minz, int& ni, int& nj, int& nk) {\n\tstd::ifstream infile(filename);\n\tinfile >> m_ni >> m_nj >> m_nk;\n\tinfile >> m_minBox[0] >> m_minBox[1] >> m_minBox[2];\n\tinfile >> m_dx;\n\n\t//std::cout << m_dx << std::endl;\n\n\tpDx = m_dx;\n\n\tni\t = m_ni;\n\tnj\t = m_nj;\n\tnk\t = m_nk;\n\tminx = m_minBox[0];\n\tminy = m_minBox[1];\n\tminz = m_minBox[2];\n\n\tstd::cout << \"load grid size \" << m_ni << \", \" << m_nj << \", \" << m_nk << std::endl;\n\n\tint gridSize = m_ni * m_nj * m_nk;\n\tm_phiGrid.resize(gridSize);\n\tfor(int i = 0; i < gridSize; ++i) {\n\t\tinfile >> m_phiGrid[i];\n\t}\n\tinfile.close();\n}\n\nvoid SampleGenerator::GeneratePoissonSamples(int length, int width, int height, float scale, int outputSamplesNumber, std::vector& outputSamples, int inputScale) {\n\tint numSamples = outputSamplesNumber;\n\n\tstd::cout << \"Generate input \" << numSamples * inputScale << \" samples...\";\n\tstd::vector inputPoints(numSamples * inputScale);\n\tfor(size_t i = 0; i < inputPoints.size(); i++) {\n\t\tinputPoints[i].x = (float) rand() / RAND_MAX * length;\n\t\tinputPoints[i].y = (float) rand() / RAND_MAX * width;\n\t\tinputPoints[i].z = (float) rand() / RAND_MAX * height;\n\t}\n\tstd::cout << \"done\\n\";\n\n\tstd::cout << \"Eliminate samples...\";\n\tstd::vector tmpPoints;\n\ttmpPoints.resize(numSamples);\n\tm_wse.Eliminate(inputPoints.data(), inputPoints.size(), tmpPoints.data(), tmpPoints.size());\n\tstd::cout << \"done\\n\";\n\n\tfor(int i = 0; i < (int) tmpPoints.size(); i++) {\n\t\toutputSamples.push_back(tmpPoints[i].x * scale);\n\t\toutputSamples.push_back(tmpPoints[i].y * scale);\n\t\toutputSamples.push_back(tmpPoints[i].z * scale);\n\t}\n}\n\nvoid SampleGenerator::GeneratePoissonSamples(float samplesPerVol, std::vector& outputSamples, int inputScale) {\n\tint numSamples = m_phiGrid.size() * samplesPerVol;\n\n\tstd::cout << \"Generate input \" << numSamples * inputScale << \" samples...\";\n\tstd::vector inputPoints(numSamples * inputScale);\n\tfor(size_t i = 0; i < inputPoints.size(); i++) {\n\t\tinputPoints[i].x = (float) rand() / RAND_MAX * (m_ni - 1);\n\t\tinputPoints[i].y = (float) rand() / RAND_MAX * (m_nj - 1);\n\t\tinputPoints[i].z = (float) rand() / RAND_MAX * (m_nk - 1);\n\t}\n\tstd::cout << \"done\\n\";\n\n\tstd::cout << \"Eliminate samples...\";\n\tstd::vector tmpPoints;\n\ttmpPoints.resize(numSamples);\n\tm_wse.Eliminate(inputPoints.data(), inputPoints.size(), tmpPoints.data(), tmpPoints.size());\n\tstd::cout << \"done\\n\";\n\n\toutputSamples.clear();\n\tfor(int i = 0; i < (int) tmpPoints.size(); i++) {\n\t\tif(fetchGridTrilinear(tmpPoints[i].x, tmpPoints[i].y, tmpPoints[i].z) < 0) {\n\t\t\toutputSamples.push_back(tmpPoints[i].x);\n\t\t\toutputSamples.push_back(tmpPoints[i].y);\n\t\t\toutputSamples.push_back(tmpPoints[i].z);\n\t\t}\n\t}\n}\n\n#\tif 1\nint SampleGenerator::GenerateUniformSamples(float samplesPerCell, std::vector& outputSamples) {\n\t// get total sample number\n\tint validCellNum = 0;\n\tfor(int i = 0; i < m_ni - 1; i++) {\n\t\tfor(int j = 0; j < m_nj - 1; j++) {\n\t\t\tfor(int k = 0; k < m_nk - 1; k++) {\n\t\t\t\tif(fetchGrid(i, j, k) < 0 || fetchGrid(i, j, k + 1) < 0 || fetchGrid(i, j + 1, k) < 0 || fetchGrid(i, j + 1, k + 1) < 0 || fetchGrid(i + 1, j, k) < 0 || fetchGrid(i + 1, j, k + 1) < 0 || fetchGrid(i + 1, j + 1, k) < 0 || fetchGrid(i + 1, j + 1, k + 1) < 0)\n\t\t\t\t\tvalidCellNum++;\n\t\t\t}\n\t\t}\n\t}\n\n\tint sampleNum = validCellNum * samplesPerCell;\n\n\tfor(int i = 0; i < sampleNum; i++) {\n\t\tcyPoint3f tmpPoint;\n\t\tdo {\n\t\t\ttmpPoint.x = (float) rand() / RAND_MAX * (m_ni - 1);\n\t\t\ttmpPoint.y = (float) rand() / RAND_MAX * (m_nj - 1);\n\t\t\ttmpPoint.z = (float) rand() / RAND_MAX * (m_nk - 1);\n\t\t} while(fetchGridTrilinear(tmpPoint.x, tmpPoint.y, tmpPoint.z) >= 0);\n\n\t\toutputSamples.push_back(tmpPoint.x);\n\t\toutputSamples.push_back(tmpPoint.y);\n\t\toutputSamples.push_back(tmpPoint.z);\n\t}\n\n\treturn sampleNum;\n}\n#\tendif\n\nvoid SampleGenerator::test() {\n\t/* std::vector< cy::Point3f > inputPoints(160000);*/\n\t//for (size_t i = 0; i < inputPoints.size(); i++) {\n\t//inputPoints[i].x = (float)rand() / RAND_MAX;\n\t//inputPoints[i].y = (float)rand() / RAND_MAX;\n\t//inputPoints[i].z = (float)rand() / RAND_MAX;\n\t//}\n\n\t//std::vector< cy::Point3f > outputPoints(32000);\n\t//std::clock_t start;\n\t//double duration;\n\t//start = std::clock();\n\t//m_dx = m_wse.Eliminate(inputPoints.data(), inputPoints.size(),\n\t//outputPoints.data(), outputPoints.size());\n\n\t//duration = (std::clock() - start) / (double)CLOCKS_PER_SEC;\n\t//std::cout << \"time = \" << duration << '\\n';\n\n\t//float minRadius = 255;\n\t//for (int i = 0; i < 12000; i++)\n\t//for (int j = 0; j < 12000; j++)\n\t//{\n\t//if (i == j) continue;\n\t//float tmp = (outputPoints[i] - outputPoints[j]).Length();\n\t//minRadius = fminf(minRadius, tmp);\n\t//}\n\t//std::cout << \"min radius = \" << minRadius << std::endl;\n\t//std::cout << m_dx << std::endl;\n\t/*std::cout << minRadius / m_dx << std::endl;*/\n\n\t//int gNi = 10, gNj = 10, gNk = 10;\n\t//int samplesPerSubcell = 12;\n\t//int inputScale = 5;\n\n\t//int sampleVolume = gNi * gNj * gNk;\n\t//int inputSampleCount = sampleVolume * samplesPerSubcell * inputScale;\n\t//int outputSampleCount = sampleVolume * samplesPerSubcell;\n\n\t//std::vector inputSamples;\n\t//inputSamples.resize(inputSampleCount);\n\n\t//int c = 0;\n\t//for (int i = 0; i < gNi; i++) for (int j = 0; j < gNj; j++) for (int k = 0; k < gNk; k++)\n\t//\tfor (int si = 0; si < samplesPerSubcell * inputScale; si++)\n\t//\t{\n\t//\t\tinputSamples[c][0] = (float)rand() / RAND_MAX;\n\t//\t\tinputSamples[c][1] = (float)rand() / RAND_MAX;\n\t//\t\tinputSamples[c][2] = (float)rand() / RAND_MAX;\n\t//\t\tc++;\n\t//\t}\n\n\t//std::vector tmpPoints;\n\t//tmpPoints.resize(outputSampleCount);\n\t//m_wse.Eliminate(inputSamples.data(), inputSamples.size(), tmpPoints.data(), tmpPoints.size());\n\n\t//float minRadius = 255;\n\t//for (int i = 0; i < outputSampleCount; i++)\n\t//\tfor (int j = 0; j < outputSampleCount; j++)\n\t//\t{\n\t//\t\tif (i == j) continue;\n\t//\t\tfloat tmp = (tmpPoints[i] - tmpPoints[j]).Length();\n\t//\t\tminRadius = fminf(minRadius, tmp);\n\t//\t}\n\t//std::cout << \"min radius = \" << minRadius << std::endl;\n}\n#else\n#\tinclude \n\n#\tinclude \n#\tinclude \n#\tinclude \n#\tinclude \n#\tinclude \n\n#\tinclude \"cyPoint.h\"\n#\tinclude \"cySampleElim.h\"\n\nclass SampleGenerator {\n public:\n\tSampleGenerator();\n\t~SampleGenerator();\n\n\tvoid test();\n\tvoid LoadSDF(std::string filename);\n\tvoid GeneratePoissonSamples(int samplesPerVol, std::vector& outputSamples, int inputScale = 5);\n\n\tint GenerateUniformSamples(int samplesPerVol, std::vector& outputSamples);\n\n protected:\n\tinline float fetchGrid(int i, int j, int k) {\n\t\treturn m_phiGrid[i + m_ni * (j + m_nj * k)];\n\t}\n\tinline float fetchGridTrilinear(float x, float y, float z) {\n\t\tfloat dx = x - floor(x);\n\t\tfloat dy = y - floor(y);\n\t\tfloat dz = z - floor(z);\n\n\t\tfloat c000 = fetchGrid((int) floor(x), (int) floor(y), (int) floor(z));\n\t\tfloat c001 = fetchGrid((int) floor(x), (int) floor(y), (int) ceil(z));\n\t\tfloat c010 = fetchGrid((int) floor(x), (int) ceil(y), (int) floor(z));\n\t\tfloat c011 = fetchGrid((int) floor(x), (int) ceil(y), (int) ceil(z));\n\t\tfloat c100 = fetchGrid((int) ceil(x), (int) floor(y), (int) floor(z));\n\t\tfloat c101 = fetchGrid((int) ceil(x), (int) floor(y), (int) ceil(z));\n\t\tfloat c110 = fetchGrid((int) ceil(x), (int) ceil(y), (int) floor(z));\n\t\tfloat c111 = fetchGrid((int) ceil(x), (int) ceil(y), (int) ceil(z));\n\n\t\tfloat c00 = c000 * (1 - dx) + c100 * dx;\n\t\tfloat c01 = c001 * (1 - dx) + c101 * dx;\n\t\tfloat c10 = c010 * (1 - dx) + c110 * dx;\n\t\tfloat c11 = c011 * (1 - dx) + c111 * dx;\n\n\t\tfloat c0 = c00 * (1 - dy) + c10 * dy;\n\t\tfloat c1 = c01 * (1 - dy) + c11 * dy;\n\n\t\treturn c0 * (1 - dz) + c1 * dz;\n\t}\n\n private:\n\tint m_ni, m_nj, m_nk;\n\tfloat m_dx;\n\tint m_padding;\n\tcyPoint3f m_minBox;\n\tstd::vector m_phiGrid;\n\tcy::WeightedSampleElimination m_wse;\n};\n\nSampleGenerator::SampleGenerator() {}\n\nSampleGenerator::~SampleGenerator() {}\n\nvoid SampleGenerator::LoadSDF(std::string filename) {\n\tstd::ifstream infile(filename);\n\tinfile >> m_ni >> m_nj >> m_nk;\n\tinfile >> m_minBox[0] >> m_minBox[1] >> m_minBox[2];\n\tinfile >> m_dx;\n\n\tstd::cout << \"load grid size \" << m_ni << \", \" << m_nj << \", \" << m_nk << std::endl;\n\n\tint gridSize = m_ni * m_nj * m_nk;\n\tm_phiGrid.resize(gridSize);\n\tfor(int i = 0; i < gridSize; ++i) {\n\t\tinfile >> m_phiGrid[i];\n\t}\n\tinfile.close();\n}\n\nvoid SampleGenerator::GeneratePoissonSamples(int samplesPerVol, std::vector& outputSamples, int inputScale) {\n\tint numSamples = m_phiGrid.size() * samplesPerVol;\n\n\tstd::cout << \"Generate input \" << numSamples * inputScale << \" samples...\";\n\tstd::vector inputPoints(numSamples * inputScale);\n\tfor(size_t i = 0; i < inputPoints.size(); i++) {\n\t\tinputPoints[i].x = (float) rand() / RAND_MAX * (m_ni - 1);\n\t\tinputPoints[i].y = (float) rand() / RAND_MAX * (m_nj - 1);\n\t\tinputPoints[i].z = (float) rand() / RAND_MAX * (m_nk - 1);\n\t}\n\tstd::cout << \"done\\n\";\n\n\tstd::cout << \"Eliminate samples...\";\n\tstd::vector tmpPoints;\n\ttmpPoints.resize(numSamples);\n\tm_wse.Eliminate(inputPoints.data(), inputPoints.size(), tmpPoints.data(), tmpPoints.size());\n\tstd::cout << \"done\\n\";\n\n\toutputSamples.clear();\n\tfor(int i = 0; i < (int) tmpPoints.size(); i++) {\n\t\tif(fetchGridTrilinear(tmpPoints[i].x, tmpPoints[i].y, tmpPoints[i].z) < 0) {\n\t\t\toutputSamples.push_back(tmpPoints[i].x);\n\t\t\toutputSamples.push_back(tmpPoints[i].y);\n\t\t\toutputSamples.push_back(tmpPoints[i].z);\n\t\t}\n\t}\n}\n\nint SampleGenerator::GenerateUniformSamples(int samplesPerCell, std::vector& outputSamples) {\n\t// get total sample number\n\tint validCellNum = 0;\n\tfor(int i = 0; i < m_ni - 1; i++) {\n\t\tfor(int j = 0; j < m_nj - 1; j++) {\n\t\t\tfor(int k = 0; k < m_nk - 1; k++) {\n\t\t\t\tif(fetchGrid(i, j, k) < 0 || fetchGrid(i, j, k + 1) < 0 || fetchGrid(i, j + 1, k) < 0 || fetchGrid(i, j + 1, k + 1) < 0 || fetchGrid(i + 1, j, k) < 0 || fetchGrid(i + 1, j, k + 1) < 0 || fetchGrid(i + 1, j + 1, k) < 0 || fetchGrid(i + 1, j + 1, k + 1) < 0)\n\t\t\t\t\tvalidCellNum++;\n\t\t\t}\n\t\t}\n\t}\n\n\tint sampleNum = validCellNum * samplesPerCell;\n\n\tfor(int i = 0; i < sampleNum; i++) {\n\t\tcyPoint3f tmpPoint;\n\t\tdo {\n\t\t\ttmpPoint.x = (float) rand() / RAND_MAX * (m_ni - 1);\n\t\t\ttmpPoint.y = (float) rand() / RAND_MAX * (m_nj - 1);\n\t\t\ttmpPoint.z = (float) rand() / RAND_MAX * (m_nk - 1);\n\t\t} while(fetchGridTrilinear(tmpPoint.x, tmpPoint.y, tmpPoint.z) >= 0);\n\n\t\toutputSamples.push_back(tmpPoint.x);\n\t\toutputSamples.push_back(tmpPoint.y);\n\t\toutputSamples.push_back(tmpPoint.z);\n\t}\n\n\treturn sampleNum;\n}\n\nvoid SampleGenerator::test() {\n\tstd::vector inputPoints(160000);\n\tfor(size_t i = 0; i < inputPoints.size(); i++) {\n\t\tinputPoints[i].x = (float) rand() / RAND_MAX;\n\t\tinputPoints[i].y = (float) rand() / RAND_MAX;\n\t\tinputPoints[i].z = (float) rand() / RAND_MAX;\n\t}\n\n\tstd::vector outputPoints(32000);\n\tstd::clock_t start;\n\tdouble duration;\n\tstart = std::clock();\n\tm_wse.Eliminate(inputPoints.data(), inputPoints.size(), outputPoints.data(), outputPoints.size());\n\n\tduration = (std::clock() - start) / (double) CLOCKS_PER_SEC;\n\tstd::cout << \"time = \" << duration << '\\n';\n\n\tfloat minRadius = 255;\n\tfor(int i = 0; i < 12000; i++)\n\t\tfor(int j = 0; j < 12000; j++) {\n\t\t\tif(i == j)\n\t\t\t\tcontinue;\n\t\t\tfloat tmp = (outputPoints[i] - outputPoints[j]).Length();\n\t\t\tminRadius = fminf(minRadius, tmp);\n\t\t}\n\tstd::cout << \"min radius = \" << minRadius << std::endl;\n\n\t//int gNi = 10, gNj = 10, gNk = 10;\n\t//int samplesPerSubcell = 12;\n\t//int inputScale = 5;\n\n\t//int sampleVolume = gNi * gNj * gNk;\n\t//int inputSampleCount = sampleVolume * samplesPerSubcell * inputScale;\n\t//int outputSampleCount = sampleVolume * samplesPerSubcell;\n\n\t//std::vector inputSamples;\n\t//inputSamples.resize(inputSampleCount);\n\n\t//int c = 0;\n\t//for (int i = 0; i < gNi; i++) for (int j = 0; j < gNj; j++) for (int k = 0; k < gNk; k++)\n\t//\tfor (int si = 0; si < samplesPerSubcell * inputScale; si++)\n\t//\t{\n\t//\t\tinputSamples[c][0] = (float)rand() / RAND_MAX;\n\t//\t\tinputSamples[c][1] = (float)rand() / RAND_MAX;\n\t//\t\tinputSamples[c][2] = (float)rand() / RAND_MAX;\n\t//\t\tc++;\n\t//\t}\n\n\t//std::vector tmpPoints;\n\t//tmpPoints.resize(outputSampleCount);\n\t//m_wse.Eliminate(inputSamples.data(), inputSamples.size(), tmpPoints.data(), tmpPoints.size());\n\n\t//float minRadius = 255;\n\t//for (int i = 0; i < outputSampleCount; i++)\n\t//\tfor (int j = 0; j < outputSampleCount; j++)\n\t//\t{\n\t//\t\tif (i == j) continue;\n\t//\t\tfloat tmp = (tmpPoints[i] - tmpPoints[j]).Length();\n\t//\t\tminRadius = fminf(minRadius, tmp);\n\t//\t}\n\t//std::cout << \"min radius = \" << minRadius << std::endl;\n}\n#endif\n" }, { "path": "Library/MnSystem/IO/PoissonDisk/cyCore.h", "content": "// cyCodeBase by Cem Yuksel\n// [www.cemyuksel.com]\n//-------------------------------------------------------------------------------\n//! \\file cyCore.h\n//! \\author Cem Yuksel\n//!\n//! \\brief Core functions and macros\n//!\n//! Core functions and macros for math and other common operations\n//!\n//-------------------------------------------------------------------------------\n//\n// Copyright (c) 2016, Cem Yuksel \n// All rights reserved.\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n//\n// The above copyright notice and this permission notice shall be included in all\n// copies or substantial portions of the Software.\n//\n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\n// SOFTWARE.\n//\n//-------------------------------------------------------------------------------\n\n#ifndef _CY_CORE_H_INCLUDED_\n#define _CY_CORE_H_INCLUDED_\n\n//-------------------------------------------------------------------------------\n\n#ifndef _CY_CORE_MEMCPY_LIMIT\n#\tdefine _CY_CORE_MEMCPY_LIMIT 256\n#endif\n\n//-------------------------------------------------------------------------------\n\n#include \n#include \n#include \n#include \n\n#include \n\n//-------------------------------------------------------------------------------\n//////////////////////////////////////////////////////////////////////////\n// Compiler compatibility\n//////////////////////////////////////////////////////////////////////////\n\n#if defined(__INTEL_COMPILER)\n#\tdefine _CY_COMPILER_INTEL __INTEL_COMPILER\n#\tdefine _CY_COMPILER_VER_MEETS(msc, gcc, clang, intel) _CY_COMPILER_INTEL >= intel\n#\tdefine _CY_COMPILER_VER_BELOW(msc, gcc, clang, intel) _CY_COMPILER_INTEL < intel\n#elif defined(__clang__)\n#\tdefine _CY_COMPILER_CLANG (__clang_major__ * 10000 + __clang_minor__ * 100 + __clang_patchlevel__)\n#\tdefine _CY_COMPILER_VER_MEETS(msc, gcc, clang, intel) _CY_COMPILER_CLANG >= clang\n#\tdefine _CY_COMPILER_VER_BELOW(msc, gcc, clang, intel) _CY_COMPILER_CLANG < clang\n#elif defined(_MSC_VER)\n#\tdefine _CY_COMPILER_MSC _MSC_VER\n#\tdefine _CY_COMPILER_VER_MEETS(msc, gcc, clang, intel) _CY_COMPILER_MSC >= msc\n#\tdefine _CY_COMPILER_VER_BELOW(msc, gcc, clang, intel) _CY_COMPILER_MSC < msc\n#elif __GNUC__\n#\tdefine _CY_COMPILER_GCC (__GNUC__ * 10000 + __GNUC_MINOR__ * 100 + __GNUC_PATCHLEVEL__)\n#\tdefine _CY_COMPILER_VER_MEETS(msc, gcc, clang, intel) _CY_COMPILER_GCC >= gcc\n#\tdefine _CY_COMPILER_VER_BELOW(msc, gcc, clang, intel) _CY_COMPILER_GCC < gcc\n#else\n#\tdefine _CY_COMPILER_UNKNOWN\n#\tdefine _CY_COMPILER_VER_MEETS(msc, gcc, clang, intel) false\n#\tdefine _CY_COMPILER_VER_BELOW(msc, gcc, clang, intel) false\n#endif\n\n// constexpr\n#ifndef __cpp_constexpr\n#\tif _CY_COMPILER_VER_MEETS(1900, 40600, 30100, 1310)\n#\t\tdefine __cpp_constexpr\n#\telse\n#\t\tdefine constexpr\n#\tendif\n#endif\n\n// nullptr\n#if _CY_COMPILER_VER_BELOW(1600, 40600, 20900, 1210)\nclass _cy_nullptr_t {\n public:\n\ttemplate\n\toperator T*() const {\n\t\treturn 0;\n\t}\n\ttemplate\n\toperator T C::*() const {\n\t\treturn 0;\n\t}\n\n private:\n\tvoid operator&() const {}\n};\nstatic _cy_nullptr_t nullptr;\n#endif\n\n// template aliases\n#define _CY_TEMPLATE_ALIAS_UNPACK(...) __VA_ARGS__\n#if _CY_COMPILER_VER_BELOW(1800, 40700, 30000, 1210)\n#\tdefine _CY_TEMPLATE_ALIAS(template_name, template_equivalent) \\\n\t\tclass template_name : public _CY_TEMPLATE_ALIAS_UNPACK template_equivalent {}\n#else\n#\tdefine _CY_TEMPLATE_ALIAS(template_name, template_equivalent) using template_name = _CY_TEMPLATE_ALIAS_UNPACK template_equivalent\n#endif\n\n// std::is_trivially_copyable\n#if _CY_COMPILER_VER_MEETS(1700, 50000, 30400, 1300)\n#\tdefine _cy_std_is_trivially_copyable 1\n#endif\n\n//////////////////////////////////////////////////////////////////////////\n// Auto Vectorization\n//////////////////////////////////////////////////////////////////////////\n\n#ifdef _MSC_VER\n#\tif _MSC_VER >= 1700\n#\t\tdefine _CY_IVDEP __pragma(loop(ivdep))\n#\tendif\n#elif defined __GNUC__\n#\tif _CY_GCC_VER >= 40900\n#\t\tdefine _CY_IVDEP _Pragma(\"GCC ivdep\");\n#\tendif\n#elif defined __clang__\n#\tif _CY_CLANG_VER >= 30500\n#\t\tdefine _CY_IVDEP _Pragma(\"clang loop vectorize(enable) interleave(enable)\");\n#\tendif\n#else\n//# define _CY_IVDEP _Pragma(\"ivdep\");\n#\tdefine _CY_IVDEP\n#endif\n\n#ifndef _CY_IVDEP\n#\tdefine _CY_IVDEP\n#endif\n\n#define _CY_IVDEP_FOR _CY_IVDEP for\n\n//////////////////////////////////////////////////////////////////////////\n//-------------------------------------------------------------------------------\nnamespace cy {\n//-------------------------------------------------------------------------------\n//////////////////////////////////////////////////////////////////////////\n// Math functions\n//////////////////////////////////////////////////////////////////////////\n\n//!@name Common math function templates\n\ntemplate\ninline TYPE cySin(TYPE a) {\n\treturn (TYPE)::sin(a);\n}\ntemplate\ninline TYPE cyCos(TYPE a) {\n\treturn (TYPE)::cos(a);\n}\ntemplate\ninline TYPE cyTan(TYPE a) {\n\treturn (TYPE)::tan(a);\n}\ntemplate\ninline TYPE cyAbs(TYPE a) {\n\treturn (TYPE)::abs(a);\n}\ntemplate\ninline TYPE cySqrt(TYPE a) {\n\treturn (TYPE)::sqrt((double) a);\n}\ntemplate\ninline TYPE cyPow(TYPE a, TYPE e) {\n\treturn (TYPE)::pow(a, e);\n}\ntemplate\ninline TYPE cyPi() {\n\treturn TYPE(3.141592653589793238462643383279502884197169);\n}\n\ntemplate<>\ninline float cySin(float a) {\n\treturn ::sinf(a);\n}\ntemplate<>\ninline float cyCos(float a) {\n\treturn ::cosf(a);\n}\ntemplate<>\ninline float cyTan(float a) {\n\treturn ::tanf(a);\n}\ntemplate<>\ninline float cyAbs(float a) {\n\treturn ::fabsf(a);\n}\ntemplate<>\ninline float cySqrt(float a) {\n\treturn ::sqrtf(a);\n}\ntemplate<>\ninline float cyPow(float a, float e) {\n\treturn ::powf(a, e);\n}\n\ntemplate<>\ninline double cyAbs(double a) {\n\treturn ::fabs(a);\n}\n\n//////////////////////////////////////////////////////////////////////////\n// Memory Operations\n//////////////////////////////////////////////////////////////////////////\n\n#ifdef _cy_std_is_trivially_copyable\n#\tdefine CY_MEMCOPY(type, dest, source, n) \\\n\t\t{ \\\n\t\t\tif(!std::is_trivially_copyable() || (n) * sizeof(type) < _CY_CORE_MEMCPY_LIMIT) { \\\n\t\t\t\tfor(int i = 0; i < (n); i++) \\\n\t\t\t\t\t(dest)[i] = (source)[i]; \\\n\t\t\t} else { \\\n\t\t\t\tmemcpy(dest, source, (n) * sizeof(type)); \\\n\t\t\t} \\\n\t\t}\n#else\n#\tdefine CY_MEMCOPY(type, dest, source, n) \\\n\t\t{ \\\n\t\t\tfor(int i = 0; i < (n); i++) \\\n\t\t\t\t(dest)[i] = (source)[i]; \\\n\t\t}\n#endif\n\n#define CY_MEMCONVERT(type, dest, source, n) \\\n\t{ \\\n\t\tfor(int i = 0; i < (n); i++) \\\n\t\t\t(dest)[i] = type((source)[i]); \\\n\t}\n\n#define CY_MEMCLEAR(type, dest, n) memset(dest, 0, (n) * sizeof(type))\n\n//////////////////////////////////////////////////////////////////////////\n\n//-------------------------------------------------------------------------------\n}// namespace cy\n//-------------------------------------------------------------------------------\n\n#endif\n" }, { "path": "Library/MnSystem/IO/PoissonDisk/cyHeap.h", "content": "// cyCodeBase by Cem Yuksel\n// [www.cemyuksel.com]\n//-------------------------------------------------------------------------------\n//! \\file cyHeap.h\n//! \\author Cem Yuksel\n//!\n//! \\brief A general-purpose heap class\n//!\n//! This file includes a general-purpose heap class.\n//!\n//-------------------------------------------------------------------------------\n//\n// Copyright (c) 2016, Cem Yuksel \n// All rights reserved.\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n//\n// The above copyright notice and this permission notice shall be included in all\n// copies or substantial portions of the Software.\n//\n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\n// SOFTWARE.\n//\n//-------------------------------------------------------------------------------\n\n#ifndef _CY_HEAP_H_INCLUDED_\n#define _CY_HEAP_H_INCLUDED_\n\n//-------------------------------------------------------------------------------\n\n#include \n#include \n\n//-------------------------------------------------------------------------------\nnamespace cy {\n//-------------------------------------------------------------------------------\n\n//! A general-purpose max-heap structure that allows random access and updates.\n//!\n//! The main data can be kept in an external array or within the Heap class.\n\ntemplate\nclass Heap {\n public:\n\t//////////////////////////////////////////////////////////////////////////!//!//!\n\t//!@name Constructor and Destructor\n\n\tHeap()\n\t\t: size(0)\n\t\t, heapItemCount(0)\n\t\t, data(nullptr)\n\t\t, heap(nullptr)\n\t\t, heapPos(nullptr)\n\t\t, deleteData(false) {}\n\t~Heap() {\n\t\tClear();\n\t}\n\n\t//////////////////////////////////////////////////////////////////////////!//!//!\n\t//!@name Initialization methods\n\n\t//! Deletes all data owned by the class.\n\tvoid Clear() {\n\t\tClearData();\n\t\tClearHeap();\n\t}\n\n\t//! Copies the main data items from an array into the internal storage of this class.\n\tvoid CopyData(const DATA_TYPE* items, SIZE_TYPE itemCount) {\n\t\tClearData();\n\t\tsize = itemCount;\n\t\tdata = new DATA_TYPE[size];\n\t\tfor(SIZE_TYPE i = 0; i < size; i++)\n\t\t\tdata[i] = items[i];\n\t\tdeleteData = true;\n\t}\n\n\t//! Moves the main data items from an array to the internal storage of this class.\n\t//! Modifying this array externally can invalidate the heap structure.\n\t//! The given array must NOT be deleted externally.\n\t//! The given items pointer still points to the same data, but the class claims\n\t//! ownership of the data. Therefore, when the class object is deleted, the data\n\t//! items are deleted as well. If this is not desirable, use SetDataPointer.\n\tvoid MoveData(DATA_TYPE* items, SIZE_TYPE itemCount) {\n\t\tClearData();\n\t\tdata\t = items;\n\t\tsize\t = itemCount;\n\t\tdeleteData = true;\n\t}\n\n\t//! Sets the data pointer of this class. This method is used for sharing the items\n\t//! array with other structures. Unlike setting the main data using the MoveData\n\t//! method, when SetDataPointer is used, the class does NOT claim ownership\n\t//! of the data. Therefore, it does not deallocate memory used for the main data\n\t//! when it is deleted, and the data items must be deleted externally.\n\t//! However, the data items must NOT be deleted while an object of this class is used.\n\tvoid SetDataPointer(DATA_TYPE* items, SIZE_TYPE itemCount) {\n\t\tClearData();\n\t\tdata\t = items;\n\t\tsize\t = itemCount;\n\t\tdeleteData = false;\n\t}\n\n\t//! The Build method builds the heap structure using the main data. Therefore,\n\t//! the main data must be set using either CopyData, MoveData, or SetDataPointer\n\t//! before calling the Build method.\n\tvoid Build() {\n\t\tClearHeap();\n\t\theapItemCount = size;\n\t\theap\t\t = new SIZE_TYPE[size + 1];\n\t\theapPos\t\t = new SIZE_TYPE[size];\n\t\tfor(SIZE_TYPE i = 0; i < heapItemCount; i++)\n\t\t\theapPos[i] = i + 1;\n\t\tfor(SIZE_TYPE i = 1; i <= heapItemCount; i++)\n\t\t\theap[i] = i - 1;\n\t\tif(heapItemCount <= 1)\n\t\t\treturn;\n\t\tfor(SIZE_TYPE ix = heapItemCount / 2; ix > 0; ix--)\n\t\t\tHeapMoveDown(ix);\n\t}\n\n\t//////////////////////////////////////////////////////////////////////////!//!//!\n\t//!@name Access and manipulation methods\n\n\t//! Returns the item from the main data with the given id.\n\tconst DATA_TYPE& GetItem(SIZE_TYPE id) const {\n\t\tassert(id < size);\n\t\treturn data[id];\n\t}\n\n\t//! Sets the item with the given id and updates the heap structure accordingly.\n\t//! Returns false if the item is not in the heap anymore (removed by Pop) or if its heap position is not changed.\n\tbool SetItem(SIZE_TYPE id, const DATA_TYPE& item) {\n\t\tassert(id < size);\n\t\tdata[id] = item;\n\t\treturn MoveItem(id);\n\t}\n\n\t//! Moves the item with the given id to the correct position in the heap.\n\t//! This method is useful for fixing the heap position after an item is modified externally.\n\t//! Returns false if the item is not in the heap anymore (removed by Pop) or if its heap position is not changed.\n\tbool MoveItem(SIZE_TYPE id) {\n\t\treturn HeapOrder(heapPos[id]);\n\t}\n\n\t//! Moves the item with the given id towards the top of the heap.\n\t//! This method is useful for fixing the heap position after an item is modified externally to increase its priority.\n\t//! Returns false if the item is not in the heap anymore (removed by Pop) or if its heap position is not changed.\n\tbool MoveItemUp(SIZE_TYPE id) {\n\t\treturn HeapMoveUp(heapPos[id]);\n\t}\n\n\t//! Moves the item with the given id towards the top of the heap.\n\t//! This method is useful for fixing the heap position after an item is modified externally to decrease its priority.\n\t//! Returns false if the item is not in the heap anymore (removed by Pop) or if its heap position is not changed.\n\tbool MoveItemDown(SIZE_TYPE id) {\n\t\treturn HeapMoveDown(heapPos[id]);\n\t}\n\n\t//! Returns if the item with the given id is in the heap or removed by Pop.\n\tbool IsInHeap(SIZE_TYPE id) const {\n\t\tassert(id < size);\n\t\treturn heapPos[id] <= heapItemCount;\n\t}\n\n\t//! Returns the number of items in the heap.\n\tSIZE_TYPE NumItemsInHeap() const {\n\t\treturn heapItemCount;\n\t}\n\n\t//! Returns the item from the heap with the given heap position.\n\t//! Note that items that are removed from the heap appear in the inverse order\n\t//! with which they were removed after the last item in the heap.\n\tconst DATA_TYPE& GetFromHeap(SIZE_TYPE heapIndex) const {\n\t\tassert(heapIndex < size);\n\t\treturn data[heap[heapIndex + 1]];\n\t}\n\n\t//! Returns the id of the item from the heap with the given heap position.\n\t//! Note that items that are removed from the heap appear in the inverse order\n\t//! with which they were removed after the last item in the heap.\n\tSIZE_TYPE GetIDFromHeap(SIZE_TYPE heapIndex) const {\n\t\tassert(heapIndex < size);\n\t\treturn heap[heapIndex + 1];\n\t}\n\n\t//! Returns the item at the top of the heap.\n\tconst DATA_TYPE& GetTopItem() const {\n\t\tassert(size >= 1);\n\t\treturn data[heap[1]];\n\t}\n\n\t//! Returns the id of the item at the top of the heap.\n\tSIZE_TYPE GetTopItemID() const {\n\t\tassert(size >= 1);\n\t\treturn heap[1];\n\t}\n\n\t//! Removes and returns the item at the top of the heap.\n\t//! The removed item is not deleted, but it is removed from the heap\n\t//! by placing it right after the last item in the heap.\n\tvoid Pop(DATA_TYPE& item) {\n\t\tPop();\n\t\titem = data[heap[heapItemCount]];\n\t}\n\n\t//! Removes the item at the top of the heap.\n\t//! The removed item is not deleted, but it is removed from the heap\n\t//! by placing it right after the last item in the heap.\n\tvoid Pop() {\n\t\tSwapItems(1, heapItemCount);\n\t\theapItemCount--;\n\t\tHeapMoveDown(1);\n\t}\n\n private:\n\t//////////////////////////////////////////////////////////////////////////!//!//!\n\t//!@name Internal structures and methods\n\n\tDATA_TYPE* data;\t\t// The main data pointer.\n\tSIZE_TYPE* heap;\t\t// The heap array, keeping the id of each data item.\n\tSIZE_TYPE* heapPos;\t\t// The heap position of each item.\n\tSIZE_TYPE heapItemCount;// The number of items in the heap.\n\tSIZE_TYPE size;\t\t\t// The total item count, including the ones removed from the heap.\n\tbool deleteData;\t\t// Determines whether the data pointer owns the memory it points to.\n\n\t// Clears the data pointer and deallocates memory if the data is owned.\n\tvoid ClearData() {\n\t\tif(deleteData)\n\t\t\tdelete[] data;\n\t\tdata\t = nullptr;\n\t\tdeleteData = false;\n\t\tsize\t = 0;\n\t}\n\n\t// Clears the heap structure.\n\tvoid ClearHeap() {\n\t\tdelete[] heap;\n\t\theap = nullptr;\n\t\tdelete[] heapPos;\n\t\theapPos\t\t = nullptr;\n\t\theapItemCount = 0;\n\t}\n\n\t// Checks if the item should be moved.\n\t// Returns true if the item is in the heap.\n\tbool HeapOrder(SIZE_TYPE ix) {\n\t\tif(ix > heapItemCount)\n\t\t\treturn false;\n\t\tif(HeapMoveUp(ix))\n\t\t\treturn true;\n\t\treturn HeapMoveDown(ix);// if it can't be move up, move it down\n\t}\n\n\t// Checks if the item should be moved up, returns true if the item is moved.\n\tbool HeapMoveUp(SIZE_TYPE ix) {\n\t\tSIZE_TYPE org = ix;\n\t\twhile(ix >= 2) {\n\t\t\tSIZE_TYPE parent = ix / 2;\n\t\t\tif(!IsSmaller(parent, ix))\n\t\t\t\tbreak;\n\t\t\tSwapItems(parent, ix);\n\t\t\tix = parent;\n\t\t}\n\t\treturn ix != org;\n\t}\n\n\t// Checks if the item should be moved down, returns true if the item is moved.\n\tbool HeapMoveDown(SIZE_TYPE ix) {\n\t\tSIZE_TYPE org\t= ix;\n\t\tSIZE_TYPE child = ix * 2;\n\t\twhile(child + 1 <= heapItemCount) {\n\t\t\tif(IsSmaller(child, child + 1))\n\t\t\t\tchild++;\n\t\t\tif(!IsSmaller(ix, child))\n\t\t\t\treturn ix != org;\n\t\t\tSwapItems(ix, child);\n\t\t\tix\t = child;\n\t\t\tchild = ix * 2;\n\t\t}\n\t\t// Check the very last item as well\n\t\tif(child <= heapItemCount) {\n\t\t\tif(IsSmaller(ix, child)) {\n\t\t\t\tSwapItems(ix, child);\n\t\t\t\treturn true;\n\t\t\t}\n\t\t}\n\t\treturn ix != org;\n\t}\n\n\t// Returns if the item at ix1 is smaller than the one at ix2.\n\tbool IsSmaller(SIZE_TYPE ix1, SIZE_TYPE ix2) {\n\t\treturn data[heap[ix1]] < data[heap[ix2]];\n\t}\n\n\t// Swaps the heap positions of items at ix1 and ix2.\n\tvoid SwapItems(SIZE_TYPE ix1, SIZE_TYPE ix2) {\n\t\tSIZE_TYPE t\t\t = heap[ix1];\n\t\theap[ix1]\t\t = heap[ix2];\n\t\theap[ix2]\t\t = t;\n\t\theapPos[heap[ix1]] = ix1;\n\t\theapPos[heap[ix2]] = ix2;\n\t}\n\n\t//////////////////////////////////////////////////////////////////////////!//!//!\n};\n\n//-------------------------------------------------------------------------------\n}// namespace cy\n//-------------------------------------------------------------------------------\n\n#endif\n" }, { "path": "Library/MnSystem/IO/PoissonDisk/cyPoint.h", "content": "// cyCodeBase by Cem Yuksel\n// [www.cemyuksel.com]\n//-------------------------------------------------------------------------------\n//! \\file cyPoint.h\n//! \\author Cem Yuksel\n//!\n//! \\brief 2D, 3D, 4D, and ND point classes.\n//!\n//-------------------------------------------------------------------------------\n//\n// Copyright (c) 2016, Cem Yuksel \n// All rights reserved.\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n//\n// The above copyright notice and this permission notice shall be included in all\n// copies or substantial portions of the Software.\n//\n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\n// SOFTWARE.\n//\n//-------------------------------------------------------------------------------\n\n#ifndef _CY_POINT_H_INCLUDED_\n#define _CY_POINT_H_INCLUDED_\n\n//-------------------------------------------------------------------------------\n\n#include \"cyCore.h\"\n\n//-------------------------------------------------------------------------------\nnamespace cy {\n//-------------------------------------------------------------------------------\n\n// Forward declarations\n//!\t\\cond HIDDEN_SYMBOLS\ntemplate\nclass Point2;\ntemplate\nclass Point3;\ntemplate\nclass Point4;\n//! \\endcond\n\n//-------------------------------------------------------------------------------\n\n//! A general class for N-dimensional points (vectors).\n\ntemplate\nclass Point {\n\tfriend Point operator+(const TYPE v, const Point& p) {\n\t\treturn p + v;\n\t}//!< Addition with a constant\n\tfriend Point operator-(const TYPE v, const Point& p) {\n\t\treturn -(p - v);\n\t}//!< Subtraction from a constant\n\tfriend Point operator*(const TYPE v, const Point& p) {\n\t\treturn p * v;\n\t}//!< Multiplication with a constant\n\n public:\n\t//!@name Components of the point/vector\n\tTYPE data[N];\n\n\t//!@name Constructors\n\tPoint() {}\n\tPoint(const Point& p) {\n\t\tCY_MEMCOPY(TYPE, data, p.data, N);\n\t}\n\texplicit Point(const TYPE* p) {\n\t\tCY_MEMCOPY(TYPE, data, p, N);\n\t}\n\texplicit Point(const TYPE& v) {\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tdata[i] = v;\n\t}\n\ttemplate\n\texplicit Point(const Point& p) {\n\t\tCY_MEMCONVERT(TYPE, data, p.data, N);\n\t}\n\ttemplate\n\texplicit Point(const Point& p) {\n\t\tif(N <= M) {\n\t\t\tCY_MEMCOPY(TYPE, data, p.data, N);\n\t\t} else {\n\t\t\tCY_MEMCOPY(TYPE, data, p.data, M);\n\t\t\tCY_MEMCLEAR(TYPE, data, N - M);\n\t\t}\n\t}\n\ttemplate\n\texplicit Point(const Point& p) {\n\t\tif(N <= M) {\n\t\t\tCY_MEMCONVERT(TYPE, data, p.data, N);\n\t\t} else {\n\t\t\tCY_MEMCONVERT(TYPE, data, p.data, M);\n\t\t\tCY_MEMCLEAR(TYPE, data, N - M);\n\t\t}\n\t}\n\texplicit Point(const Point2& p);\n\texplicit Point(const Point3& p);\n\texplicit Point(const Point4& p);\n\ttemplate\n\texplicit Point(const Point2& p);\n\ttemplate\n\texplicit Point(const Point3& p);\n\ttemplate\n\texplicit Point(const Point4& p);\n\ttemplate\n\texplicit Point(const P& p) {\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tdata[i] = (TYPE) p[i];\n\t}\n\n\t//!@name Set & Get value methods\n\tvoid Zero() {\n\t\tCY_MEMCLEAR(TYPE, data, N);\n\t}//!< Sets the coordinates as zero\n\tvoid Get(TYPE* p) const {\n\t\tCY_MEMCOPY(TYPE, p, data, N);\n\t}//!< Puts the coordinate values into the array\n\tvoid Set(const TYPE* p) {\n\t\tCY_MEMCOPY(TYPE, data, p, N);\n\t}//!< Sets the coordinates using the values in the given array\n\tvoid Set(const TYPE& v) {\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tdata[i] = v;\n\t}//!< Sets all coordinates using the given value\n\ttemplate\n\tvoid CopyData(TYPE* p) {\n\t\tif(M <= N) {\n\t\t\tCY_MEMCOPY(TYPE, p, data, M);\n\t\t} else {\n\t\t\tCY_MEMCOPY(TYPE, p, data, N);\n\t\t\tCY_MEMCLEAR(TYPE, p + N, M - N);\n\t\t}\n\t}\n\ttemplate\n\tvoid ConvertData(T* p) {\n\t\tif(M <= N) {\n\t\t\tCY_MEMCONVERT(T, p, data, M);\n\t\t} else {\n\t\t\tCY_MEMCONVERT(T, p, data, N);\n\t\t\tCY_MEMCLEAR(T, p + N, M - N);\n\t\t}\n\t}\n\n\t//!@name General methods\n\tTYPE LengthSquared() const {\n\t\tPoint p = operator*(*this);\n\t\treturn p.Sum();\n\t}//!< Returns the square of the length. Effectively, this is the dot product of the vector with itself.\n\tTYPE Length() const {\n\t\treturn (TYPE) cySqrt(LengthSquared());\n\t}//!< Returns the length of the vector.\n\tvoid Normalize() {\n\t\t*this /= Length();\n\t}//!< Normalizes the vector, such that its length becomes 1.\n\tPoint GetNormalized() const {\n\t\treturn *this / Length();\n\t}//!< Returns a normalized copy of the vector.\n\tTYPE Sum() const {\n\t\tTYPE v = data[0];\n\t\tfor(int i = 1; i < N; ++i)\n\t\t\tv += data[i];\n\t\treturn v;\n\t}//!< Returns the sum of its components\n\tbool IsZero() const {\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tif(data[i] != TYPE(0))\n\t\t\t\treturn false;\n\t\treturn true;\n\t}//!< Returns true if all components are exactly zero\n\tTYPE Min() const {\n\t\tTYPE m = data[0];\n\t\tfor(int i = 1; i < N; ++i)\n\t\t\tif(m > data[i])\n\t\t\t\tm = data[i];\n\t\treturn m;\n\t}\n\tTYPE Max() const {\n\t\tTYPE m = data[0];\n\t\tfor(int i = 1; i < N; ++i)\n\t\t\tif(m < data[i])\n\t\t\t\tm = data[i];\n\t\treturn m;\n\t}\n\tint MinID() const {\n\t\tTYPE m = data[0];\n\t\tint ix = 0;\n\t\tfor(int i = 1; i < N; ++i)\n\t\t\tif(m > data[i]) {\n\t\t\t\tm = data[i];\n\t\t\t\tix = i;\n\t\t\t}\n\t\treturn m;\n\t}\n\tint MaxID() const {\n\t\tTYPE m = data[0];\n\t\tint ix = 0;\n\t\tfor(int i = 1; i < N; ++i)\n\t\t\tif(m < data[i]) {\n\t\t\t\tm = data[i];\n\t\t\t\tix = i;\n\t\t\t}\n\t\treturn m;\n\t}\n\n\t//!@name Limit methods\n\tvoid Clamp(const TYPE& minValue, const TYPE& maxValue) {\n\t\tClampMin(minValue);\n\t\tClampMax(maxValue);\n\t}\n\tvoid ClampMin(const TYPE& v) {\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tdata[i] = (data[i] < v) ? v : data[i];\n\t}\n\tvoid ClampMax(const TYPE& v) {\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tdata[i] = (data[i] > v) ? v : data[i];\n\t}\n\tvoid Abs() {\n\t\tfor(int i = 0; i < N; i++)\n\t\t\tdata[i] = cyAbs(data[i]);\n\t}//!< Converts all negative components to positive values\n\n\t//!@name Unary operators\n\tPoint operator-() const {\n\t\tPoint r;\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tr.data[i] = -data[i];\n\t\treturn r;\n\t}\n\n\t//!@name Binary operators\n\tPoint operator+(const Point& p) const {\n\t\tPoint r;\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tr.data[i] = data[i] + p.data[i];\n\t\treturn r;\n\t}\n\tPoint operator-(const Point& p) const {\n\t\tPoint r;\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tr.data[i] = data[i] - p.data[i];\n\t\treturn r;\n\t}\n\tPoint operator*(const Point& p) const {\n\t\tPoint r;\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tr.data[i] = data[i] * p.data[i];\n\t\treturn r;\n\t}\n\tPoint operator/(const Point& p) const {\n\t\tPoint r;\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tr.data[i] = data[i] / p.data[i];\n\t\treturn r;\n\t}\n\tPoint operator+(const TYPE& v) const {\n\t\tPoint r;\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tr.data[i] = data[i] + v;\n\t\treturn r;\n\t}\n\tPoint operator-(const TYPE& v) const {\n\t\tPoint r;\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tr.data[i] = data[i] - v;\n\t\treturn r;\n\t}\n\tPoint operator*(const TYPE& v) const {\n\t\tPoint r;\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tr.data[i] = data[i] * v;\n\t\treturn r;\n\t}\n\tPoint operator/(const TYPE& v) const {\n\t\tPoint r;\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tr.data[i] = data[i] / v;\n\t\treturn r;\n\t}\n\n\t//!@name Assignment operators\n\tconst Point& operator=(const Point& p) {\n\t\tCY_MEMCOPY(TYPE, data, p.data, N);\n\t\treturn *this;\n\t}\n\tconst Point& operator+=(const Point& p) {\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tdata[i] += p.data[i];\n\t\treturn *this;\n\t}\n\tconst Point& operator-=(const Point& p) {\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tdata[i] -= p.data[i];\n\t\treturn *this;\n\t}\n\tconst Point& operator*=(const Point& p) {\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tdata[i] *= p.data[i];\n\t\treturn *this;\n\t}\n\tconst Point& operator/=(const Point& p) {\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tdata[i] /= p.data[i];\n\t\treturn *this;\n\t}\n\tconst Point& operator+=(const TYPE& v) {\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tdata[i] += v;\n\t\treturn *this;\n\t}\n\tconst Point& operator-=(const TYPE& v) {\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tdata[i] -= v;\n\t\treturn *this;\n\t}\n\tconst Point& operator*=(const TYPE& v) {\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tdata[i] *= v;\n\t\treturn *this;\n\t}\n\tconst Point& operator/=(const TYPE& v) {\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tdata[i] /= v;\n\t\treturn *this;\n\t}\n\n\t//!@name Test operators\n\tbool operator==(const Point& p) const {\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tif(data[i] != p.data[i])\n\t\t\t\treturn false;\n\t\treturn true;\n\t}\n\tbool operator!=(const Point& p) const {\n\t\tfor(int i = 0; i < N; ++i)\n\t\t\tif(data[i] != p.data[i])\n\t\t\t\treturn true;\n\t\treturn false;\n\t}\n\n\t//!@name Access operators\n\tTYPE& operator[](int i) {\n\t\treturn data[i];\n\t}\n\tTYPE operator[](int i) const {\n\t\treturn data[i];\n\t}\n\n\t//!@name Dot product\n\tTYPE Dot(const Point& p) const {\n\t\tPoint r = operator*(p);\n\t\treturn r.Sum();\n\t}//!< Dot product\n\tTYPE operator%(const Point& p) const {\n\t\treturn Dot(p);\n\t}//!< Dot product operator\n};\n\n//-------------------------------------------------------------------------------\n\n//! 2D point (vector) class\n\ntemplate\nclass Point2 {\n\tfriend Point2 operator+(const TYPE v, const Point2& p) {\n\t\treturn p + v;\n\t}//!< Addition with a constant\n\tfriend Point2 operator-(const TYPE v, const Point2& p) {\n\t\treturn -(p - v);\n\t}//!< Subtraction from a constant\n\tfriend Point2 operator*(const TYPE v, const Point2& p) {\n\t\treturn p * v;\n\t}//!< Multiplication with a constant\n\n public:\n\t//!@name Components of the point/vector\n\tTYPE x, y;\n\n\t//!@name Constructors\n\tPoint2() {}\n\n\tPoint2(const TYPE& _x, const TYPE& _y)\n\t\t: x(_x)\n\t\t, y(_y) {}\n\tPoint2(const Point2& p)\n\t\t: x(p.x)\n\t\t, y(p.y) {}\n\texplicit Point2(const TYPE& v)\n\t\t: x(v)\n\t\t, y(v) {}\n\texplicit Point2(const Point3& p);\n\texplicit Point2(const Point4& p);\n\ttemplate\n\texplicit Point2(const Point2& p)\n\t\t: x(TYPE(p.x))\n\t\t, y(TYPE(p.y)) {}\n\ttemplate\n\texplicit Point2(const Point3& p);\n\ttemplate\n\texplicit Point2(const Point4& p);\n\ttemplate\n\texplicit Point2(const Point& p) {\n\t\tp.CopyData<2>(&x);\n\t}\n\ttemplate\n\texplicit Point2(const Point& p) {\n\t\tp.template ConvertData(&x);\n\t}\n\ttemplate\n\texplicit Point2(const P& p)\n\t\t: x((TYPE) p[0])\n\t\t, y((TYPE) p[1]) {}\n\n\t//!@name Set & Get value methods\n\tvoid Zero() {\n\t\tCY_MEMCLEAR(TYPE, Data(), 2);\n\t}//!< Sets the coordinates as zero.\n\tvoid Get(TYPE* p) const {\n\t\t((Point2*) p)->operator=(*this);\n\t}//!< Puts the coordinate values into the array.\n\tvoid Set(const TYPE* p) {\n\t\toperator=(*((Point2*) p));\n\t}//!< Sets the coordinates using the values in the given array.\n\tvoid Set(const TYPE& v) {\n\t\tx = v;\n\t\ty = v;\n\t}//!< Sets all coordinates using the given value\n\tvoid Set(const TYPE& _x, const TYPE& _y) {\n\t\tx = _x;\n\t\ty = _y;\n\t}//!< Sets the coordinates using the given values\n\n\t//!@name General methods\n\tTYPE LengthSquared() const {\n\t\tPoint2 p = operator*(*this);\n\t\treturn p.Sum();\n\t}//!< Returns the square of the length. Effectively, this is the dot product of the vector with itself.\n\tTYPE Length() const {\n\t\treturn (TYPE) cySqrt(LengthSquared());\n\t}//!< Returns the length of the vector.\n\tvoid Normalize() {\n\t\t*this /= Length();\n\t}//!< Normalizes the vector, such that its length becomes 1.\n\tPoint2 GetNormalized() const {\n\t\treturn *this / Length();\n\t}//!< Returns a normalized copy of the vector.\n\tTYPE Sum() const {\n\t\treturn x + y;\n\t}//!< Returns the sum of its components\n\tbool IsZero() const {\n\t\treturn x == TYPE(0) && y == TYPE(0);\n\t}//!< Returns true if all components are exactly zero\n\tTYPE Min() const {\n\t\treturn x < y ? x : y;\n\t}\n\tTYPE Max() const {\n\t\treturn x > y ? x : y;\n\t}\n\tint MinID() const {\n\t\treturn x < y ? 0 : 1;\n\t}\n\tint MaxID() const {\n\t\treturn x > y ? 0 : 1;\n\t}\n\n\t//!@name Limit methods\n\tvoid Clamp(const TYPE& minValue, const TYPE& maxValue) {\n\t\tClampMin(minValue);\n\t\tClampMax(maxValue);\n\t}\n\tvoid ClampMin(const TYPE& v) {\n\t\tx = (x < v) ? v : x;\n\t\ty = (y < v) ? v : y;\n\t}\n\tvoid ClampMax(const TYPE& v) {\n\t\tx = (x > v) ? v : x;\n\t\ty = (y > v) ? v : y;\n\t}\n\tvoid Abs() {\n\t\tx = cyAbs(x);\n\t\ty = cyAbs(y);\n\t}//!< Converts all negative components to positive values\n\n\t//!@name Unary operators\n\tPoint2 operator-() const {\n\t\tPoint2 r;\n\t\tr.x = -x;\n\t\tr.y = -y;\n\t\treturn r;\n\t}\n\n\t//!@name Binary operators\n\tPoint2 operator+(const Point2& p) const {\n\t\tPoint2 r;\n\t\tr.x = x + p.x;\n\t\tr.y = y + p.y;\n\t\treturn r;\n\t}\n\tPoint2 operator-(const Point2& p) const {\n\t\tPoint2 r;\n\t\tr.x = x - p.x;\n\t\tr.y = y - p.y;\n\t\treturn r;\n\t}\n\tPoint2 operator*(const Point2& p) const {\n\t\tPoint2 r;\n\t\tr.x = x * p.x;\n\t\tr.y = y * p.y;\n\t\treturn r;\n\t}\n\tPoint2 operator/(const Point2& p) const {\n\t\tPoint2 r;\n\t\tr.x = x / p.x;\n\t\tr.y = y / p.y;\n\t\treturn r;\n\t}\n\tPoint2 operator+(const TYPE& v) const {\n\t\tPoint2 r;\n\t\tr.x = x + v;\n\t\tr.y = y + v;\n\t\treturn r;\n\t}\n\tPoint2 operator-(const TYPE& v) const {\n\t\tPoint2 r;\n\t\tr.x = x - v;\n\t\tr.y = y - v;\n\t\treturn r;\n\t}\n\tPoint2 operator*(const TYPE& v) const {\n\t\tPoint2 r;\n\t\tr.x = x * v;\n\t\tr.y = y * v;\n\t\treturn r;\n\t}\n\tPoint2 operator/(const TYPE& v) const {\n\t\tPoint2 r;\n\t\tr.x = x / v;\n\t\tr.y = y / v;\n\t\treturn r;\n\t}\n\n\t//!@name Assignment operators\n\tconst Point2& operator=(const Point2& p) {\n\t\tx = p.x;\n\t\ty = p.y;\n\t\treturn *this;\n\t}\n\tconst Point2& operator+=(const Point2& p) {\n\t\tx += p.x;\n\t\ty += p.y;\n\t\treturn *this;\n\t}\n\tconst Point2& operator-=(const Point2& p) {\n\t\tx -= p.x;\n\t\ty -= p.y;\n\t\treturn *this;\n\t}\n\tconst Point2& operator*=(const Point2& p) {\n\t\tx *= p.x;\n\t\ty *= p.y;\n\t\treturn *this;\n\t}\n\tconst Point2& operator/=(const Point2& p) {\n\t\tx /= p.x;\n\t\ty /= p.y;\n\t\treturn *this;\n\t}\n\tconst Point2& operator+=(const TYPE& v) {\n\t\tx += v;\n\t\ty += v;\n\t\treturn *this;\n\t}\n\tconst Point2& operator-=(const TYPE& v) {\n\t\tx -= v;\n\t\ty -= v;\n\t\treturn *this;\n\t}\n\tconst Point2& operator*=(const TYPE& v) {\n\t\tx *= v;\n\t\ty *= v;\n\t\treturn *this;\n\t}\n\tconst Point2& operator/=(const TYPE& v) {\n\t\tx /= v;\n\t\ty /= v;\n\t\treturn *this;\n\t}\n\n\t//!@name Test operators\n\tbool operator==(const Point2& p) const {\n\t\treturn x == p.x && y == p.y;\n\t}\n\tbool operator!=(const Point2& p) const {\n\t\treturn x != p.x && y != p.y;\n\t}\n\n\t//!@name Access operators\n\tTYPE& operator[](int i) {\n\t\treturn Element(i);\n\t}\n\tconst TYPE& operator[](int i) const {\n\t\treturn Element(i);\n\t}\n\tTYPE& Element(int i) {\n\t\treturn (&x)[i];\n\t}\n\tconst TYPE& Element(int i) const {\n\t\treturn (&x)[i];\n\t}\n\tTYPE* Data() {\n\t\treturn &x;\n\t}\n\tconst TYPE* Data() const {\n\t\treturn &x;\n\t}\n\n\t//!@name Cross product and dot product\n\tTYPE Cross(const Point2& p) const {\n\t\tPoint2 r(-y, x);\n\t\treturn r.Dot(p);\n\t}//!< Cross product\n\tTYPE operator^(const Point2& p) const {\n\t\treturn Cross(p);\n\t}//!< Cross product operator\n\tTYPE Dot(const Point2& p) const {\n\t\tPoint2 r = operator*(p);\n\t\treturn r.Sum();\n\t}//!< Dot product\n\tTYPE operator%(const Point2& p) const {\n\t\treturn Dot(p);\n\t}//!< Dot product operator\n};\n\n//-------------------------------------------------------------------------------\n\n//! 3D point (vector) class\n\ntemplate\nclass Point3 {\n\tfriend Point3 operator+(const TYPE v, const Point3& p) {\n\t\treturn p + v;\n\t}//!< Addition with a constant\n\tfriend Point3 operator-(const TYPE v, const Point3& p) {\n\t\treturn -(p - v);\n\t}//!< Subtraction from a constant\n\tfriend Point3 operator*(const TYPE v, const Point3& p) {\n\t\treturn p * v;\n\t}//!< Multiplication with a constant\n\n public:\n\t//!@name Components of the point/vector\n\tTYPE x, y, z;\n\n\t//!@name Constructors\n\tPoint3() {}\n\tPoint3(const TYPE& _x, const TYPE& _y, const TYPE& _z)\n\t\t: x(_x)\n\t\t, y(_y)\n\t\t, z(_z) {}\n\tPoint3(const Point3& p)\n\t\t: x(p.x)\n\t\t, y(p.y)\n\t\t, z(p.z) {}\n\texplicit Point3(const TYPE& v)\n\t\t: x(v)\n\t\t, y(v)\n\t\t, z(v) {}\n\texplicit Point3(const Point2& p, TYPE _z = 0)\n\t\t: x(p.x)\n\t\t, y(p.y)\n\t\t, z(_z) {}\n\texplicit Point3(const Point4& p);\n\ttemplate\n\texplicit Point3(const Point3& p)\n\t\t: x(TYPE(p.x))\n\t\t, y(TYPE(p.y))\n\t\t, z(TYPE(p.z)) {}\n\ttemplate\n\texplicit Point3(const Point2& p, TYPE _z = 0)\n\t\t: x(TYPE(p.x))\n\t\t, y(TYPE(p.y))\n\t\t, z(_z) {}\n\ttemplate\n\texplicit Point3(const Point4& p);\n\ttemplate\n\texplicit Point3(const Point& p) {\n\t\tp.CopyData<3>(&x);\n\t}\n\ttemplate\n\texplicit Point3(const Point& p) {\n\t\tp.template ConvertData(&x);\n\t}\n\ttemplate\n\texplicit Point3(const P& p)\n\t\t: x((TYPE) p[0])\n\t\t, y((TYPE) p[1])\n\t\t, z((TYPE) p[2]) {}\n\n\t//!@name Set & Get value methods\n\tvoid Zero() {\n\t\tCY_MEMCLEAR(TYPE, Data(), 3);\n\t}//!< Sets the coordinates as zero\n\tvoid Get(TYPE* p) const {\n\t\t((Point3*) p)->operator=(*this);\n\t}//!< Puts the coordinate values into the array\n\tvoid Set(const TYPE* p) {\n\t\toperator=(*((Point3*) p));\n\t}//!< Sets the coordinates using the values in the given array\n\tvoid Set(const TYPE& v) {\n\t\tx = v;\n\t\ty = v;\n\t\tz = v;\n\t}//!< Sets all coordinates using the given value\n\tvoid Set(const TYPE& _x, const TYPE& _y, const TYPE& _z) {\n\t\tx = _x;\n\t\ty = _y;\n\t\tz = _z;\n\t}//!< Sets the coordinates using the given values\n\n\t//!@name General methods\n\tTYPE LengthSquared() const {\n\t\tPoint3 p = operator*(*this);\n\t\treturn p.Sum();\n\t}//!< Returns the square of the length. Effectively, this is the dot product of the vector with itself.\n\tTYPE Length() const {\n\t\treturn (TYPE) cySqrt(LengthSquared());\n\t}//!< Returns the length of the vector.\n\tvoid Normalize() {\n\t\t*this /= Length();\n\t}//!< Normalizes the vector, such that its length becomes 1.\n\tPoint3 GetNormalized() const {\n\t\treturn *this / Length();\n\t}//!< Returns a normalized copy of the vector.\n\tTYPE Sum() const {\n\t\treturn x + y + z;\n\t}//!< Returns the sum of its components\n\tbool IsZero() const {\n\t\treturn x == TYPE(0) && y == TYPE(0) && z == TYPE(0);\n\t}//!< Returns true if all components are exactly zero\n\tTYPE Min() const {\n\t\treturn x < y ? (x < z ? x : z) : (y < z ? y : z);\n\t}\n\tTYPE Max() const {\n\t\treturn x > y ? (x > z ? x : z) : (y > z ? y : z);\n\t}\n\tint MinID() const {\n\t\treturn x < y ? (x < z ? 0 : 2) : (y < z ? 1 : 2);\n\t}\n\tint MaxID() const {\n\t\treturn x > y ? (x > z ? 0 : 2) : (y > z ? 1 : 2);\n\t}\n\n\t//!@name Limit methods\n\tvoid Clamp(const TYPE& minValue, const TYPE& maxValue) {\n\t\tClampMin(minValue);\n\t\tClampMax(maxValue);\n\t}\n\tvoid ClampMin(const TYPE& v) {\n\t\tx = (x < v) ? v : x;\n\t\ty = (y < v) ? v : y;\n\t\tz = (z < v) ? v : z;\n\t}\n\tvoid ClampMax(const TYPE& v) {\n\t\tx = (x > v) ? v : x;\n\t\ty = (y > v) ? v : y;\n\t\tz = (z > v) ? v : z;\n\t}\n\tvoid Abs() {\n\t\tx = cyAbs(x);\n\t\ty = cyAbs(y);\n\t\tz = cyAbs(z);\n\t}//!< Converts all negative components to positive values\n\n\t//!@name Unary operators\n\tPoint3 operator-() const {\n\t\tPoint3 r;\n\t\tr.x = -x;\n\t\tr.y = -y;\n\t\tr.z = -z;\n\t\treturn r;\n\t}\n\n\t//!@name Binary operators\n\tPoint3 operator+(const Point3& p) const {\n\t\tPoint3 r;\n\t\tr.x = x + p.x;\n\t\tr.y = y + p.y;\n\t\tr.z = z + p.z;\n\t\treturn r;\n\t}\n\tPoint3 operator-(const Point3& p) const {\n\t\tPoint3 r;\n\t\tr.x = x - p.x;\n\t\tr.y = y - p.y;\n\t\tr.z = z - p.z;\n\t\treturn r;\n\t}\n\tPoint3 operator*(const Point3& p) const {\n\t\tPoint3 r;\n\t\tr.x = x * p.x;\n\t\tr.y = y * p.y;\n\t\tr.z = z * p.z;\n\t\treturn r;\n\t}\n\tPoint3 operator/(const Point3& p) const {\n\t\tPoint3 r;\n\t\tr.x = x / p.x;\n\t\tr.y = y / p.y;\n\t\tr.z = z / p.z;\n\t\treturn r;\n\t}\n\tPoint3 operator+(const TYPE& v) const {\n\t\tPoint3 r;\n\t\tr.x = x + v;\n\t\tr.y = y + v;\n\t\tr.z = z + v;\n\t\treturn r;\n\t}\n\tPoint3 operator-(const TYPE& v) const {\n\t\tPoint3 r;\n\t\tr.x = x - v;\n\t\tr.y = y - v;\n\t\tr.z = z - v;\n\t\treturn r;\n\t}\n\tPoint3 operator*(const TYPE& v) const {\n\t\tPoint3 r;\n\t\tr.x = x * v;\n\t\tr.y = y * v;\n\t\tr.z = z * v;\n\t\treturn r;\n\t}\n\tPoint3 operator/(const TYPE& v) const {\n\t\tPoint3 r;\n\t\tr.x = x / v;\n\t\tr.y = y / v;\n\t\tr.z = z / v;\n\t\treturn r;\n\t}\n\n\t//!@name Assignment operators\n\tconst Point3& operator=(const Point3& p) {\n\t\tx = p.x;\n\t\ty = p.y;\n\t\tz = p.z;\n\t\treturn *this;\n\t}\n\tconst Point3& operator+=(const Point3& p) {\n\t\tx += p.x;\n\t\ty += p.y;\n\t\tz += p.z;\n\t\treturn *this;\n\t}\n\tconst Point3& operator-=(const Point3& p) {\n\t\tx -= p.x;\n\t\ty -= p.y;\n\t\tz -= p.z;\n\t\treturn *this;\n\t}\n\tconst Point3& operator*=(const Point3& p) {\n\t\tx *= p.x;\n\t\ty *= p.y;\n\t\tz *= p.z;\n\t\treturn *this;\n\t}\n\tconst Point3& operator/=(const Point3& p) {\n\t\tx /= p.x;\n\t\ty /= p.y;\n\t\tz /= p.z;\n\t\treturn *this;\n\t}\n\tconst Point3& operator+=(const TYPE& v) {\n\t\tx += v;\n\t\ty += v;\n\t\tz += v;\n\t\treturn *this;\n\t}\n\tconst Point3& operator-=(const TYPE& v) {\n\t\tx -= v;\n\t\ty -= v;\n\t\tz -= v;\n\t\treturn *this;\n\t}\n\tconst Point3& operator*=(const TYPE& v) {\n\t\tx *= v;\n\t\ty *= v;\n\t\tz *= v;\n\t\treturn *this;\n\t}\n\tconst Point3& operator/=(const TYPE& v) {\n\t\tx /= v;\n\t\ty /= v;\n\t\tz /= v;\n\t\treturn *this;\n\t}\n\n\t//!@name Test operators\n\tbool operator==(const Point3& p) const {\n\t\treturn x == p.x && y == p.y && z == p.z;\n\t}\n\tbool operator!=(const Point3& p) const {\n\t\treturn x != p.x && y != p.y && z != p.z;\n\t}\n\n\t//!@name Access operators\n\tTYPE& operator[](int i) {\n\t\treturn Element(i);\n\t}\n\tconst TYPE& operator[](int i) const {\n\t\treturn Element(i);\n\t}\n\tTYPE& Element(int i) {\n\t\treturn (&x)[i];\n\t}\n\tconst TYPE& Element(int i) const {\n\t\treturn (&x)[i];\n\t}\n\tTYPE* Data() {\n\t\treturn &x;\n\t}\n\tconst TYPE* Data() const {\n\t\treturn &x;\n\t}\n\n\t//!@name Cross product and dot product\n\tPoint3 Cross(const Point3& p) const {\n\t\treturn Point3(y * p.z - z * p.y, z * p.x - x * p.z, x * p.y - y * p.x);\n\t}//!< Cross product\n\tPoint3 operator^(const Point3& p) const {\n\t\treturn Cross(p);\n\t}//!< Cross product\n\tTYPE Dot(const Point3& p) const {\n\t\tPoint3 r = operator*(p);\n\t\treturn r.Sum();\n\t}//!< Dot product\n\tTYPE operator%(const Point3& p) const {\n\t\treturn Dot(p);\n\t}//!< Dot product\n\n\t//!@name Conversion Methods\n\tPoint2 XY() const {\n\t\treturn Point2(*this);\n\t}\n};\n\n//-------------------------------------------------------------------------------\n\n//! 4D point (vector) class\n\ntemplate\nclass Point4 {\n\tfriend Point4 operator+(const TYPE v, const Point4& p) {\n\t\treturn p + v;\n\t}//!< Addition with a constant\n\tfriend Point4 operator-(const TYPE v, const Point4& p) {\n\t\treturn -(p - v);\n\t}//!< Subtraction from a constant\n\tfriend Point4 operator*(const TYPE v, const Point4& p) {\n\t\treturn p * v;\n\t}//!< Multiplication with a constant\n\n public:\n\t//!@name Components of the point/vector\n\tTYPE x, y, z, w;\n\n\t//!@name Constructors\n\tPoint4() {}\n\tPoint4(const TYPE& _x, const TYPE& _y, const TYPE& _z, const TYPE& _w)\n\t\t: x(_x)\n\t\t, y(_y)\n\t\t, z(_z)\n\t\t, w(_w) {}\n\tPoint4(const Point4& p)\n\t\t: x(p.x)\n\t\t, y(p.y)\n\t\t, z(p.z)\n\t\t, w(p.w) {}\n\texplicit Point4(const TYPE& v)\n\t\t: x(v)\n\t\t, y(v)\n\t\t, z(v)\n\t\t, w(v) {}\n\texplicit Point4(const Point3& p, TYPE _w = 1)\n\t\t: x(p.x)\n\t\t, y(p.y)\n\t\t, z(p.z)\n\t\t, w(_w) {}\n\texplicit Point4(const Point2& p, TYPE _z = 0, TYPE _w = 1)\n\t\t: x(p.x)\n\t\t, y(p.y)\n\t\t, z(_z)\n\t\t, w(_w) {}\n\ttemplate\n\texplicit Point4(const Point4& p)\n\t\t: x(TYPE(p.x))\n\t\t, y(TYPE(p.y))\n\t\t, z(TYPE(p.z))\n\t\t, w(TYPE(p.w)) {}\n\ttemplate\n\texplicit Point4(const Point3& p, TYPE _w = 1)\n\t\t: x(TYPE(p.x))\n\t\t, y(TYPE(p.y))\n\t\t, z(TYPE(p.z))\n\t\t, w(_w) {}\n\ttemplate\n\texplicit Point4(const Point2& p, TYPE _z = 0, TYPE _w = 1)\n\t\t: x(TYPE(p.x))\n\t\t, y(TYPE(p.y))\n\t\t, z(_z)\n\t\t, w(_w) {}\n\ttemplate\n\texplicit Point4(const Point& p) {\n\t\tp.CopyData<4>(&x);\n\t}\n\ttemplate\n\texplicit Point4(const Point& p) {\n\t\tp.template ConvertData(&x);\n\t}\n\ttemplate\n\texplicit Point4(const P& p)\n\t\t: x((TYPE) p[0])\n\t\t, y((TYPE) p[1])\n\t\t, z((TYPE) p[2])\n\t\t, w((TYPE) p[3]) {}\n\n\t//!@name Set & Get value methods\n\tvoid Zero() {\n\t\tCY_MEMCLEAR(TYPE, Data(), 4);\n\t}//!< Sets the coordinates as zero\n\tvoid Get(TYPE* p) const {\n\t\t((Point4*) p)->operator=(*this);\n\t}//!< Puts the coordinate values into the array\n\tvoid Set(const TYPE* p) {\n\t\toperator=(*((Point4*) p));\n\t}//!< Sets the coordinates using the values in the given array\n\tvoid Set(const TYPE& v) {\n\t\tx = v;\n\t\ty = v;\n\t\tz = v;\n\t\tw = v;\n\t}//!< Sets all coordinates using the given value\n\tvoid Set(const TYPE& _x, const TYPE& _y, const TYPE& _z, const TYPE& _w = 1) {\n\t\tx = _x;\n\t\ty = _y;\n\t\tz = _z;\n\t\tw = _w;\n\t}//!< Sets the coordinates using the given values\n\n\t//!@name General methods\n\tTYPE LengthSquared() const {\n\t\tPoint4 p = operator*(*this);\n\t\treturn p.Sum();\n\t}//!< Returns the square of the length. Effectively, this is the dot product of the vector with itself.\n\tTYPE Length() const {\n\t\treturn (TYPE) cySqrt(LengthSquared());\n\t}//!< Returns the length of the vector.\n\tvoid Normalize() {\n\t\t*this /= Length();\n\t}//!< Normalizes the vector, such that its length becomes 1.\n\tPoint4 GetNormalized() const {\n\t\treturn *this / Length();\n\t}//!< Returns a normalized copy of the vector.\n\tTYPE Sum() const {\n\t\treturn x + y + z + w;\n\t}//!< Returns the sum of its components\n\tbool IsZero() const {\n\t\treturn x == TYPE(0) && y == TYPE(0) && z == TYPE(0) && w == TYPE(0);\n\t}//!< Returns true if all components are exactly zero\n\tTYPE Min() const {\n\t\tTYPE mxy = x < y ? x : y;\n\t\tTYPE mzw = z < w ? z : w;\n\t\treturn mxy < mzw ? mxy : mzw;\n\t}\n\tTYPE Max() const {\n\t\tTYPE mxy = x > y ? x : y;\n\t\tTYPE mzw = z > w ? z : w;\n\t\treturn mxy > mzw ? mxy : mzw;\n\t}\n\tint MinID() const {\n\t\tint ixy = x < y ? 0 : 1;\n\t\tint izw = z < w ? 2 : 3;\n\t\treturn (&x)[ixy] < (&x)[izw] ? ixy : izw;\n\t}\n\tint MaxID() const {\n\t\tint ixy = x > y ? 0 : 1;\n\t\tint izw = z > w ? 2 : 3;\n\t\treturn (&x)[ixy] > (&x)[izw] ? ixy : izw;\n\t}\n\n\t//!@name Limit methods\n\tvoid Clamp(const TYPE& minValue, const TYPE& maxValue) {\n\t\tClampMin(minValue);\n\t\tClampMax(maxValue);\n\t}\n\tvoid ClampMin(const TYPE& v) {\n\t\tx = (x < v) ? v : x;\n\t\ty = (y < v) ? v : y;\n\t\tz = (z < v) ? v : z;\n\t\tw = (w < v) ? v : w;\n\t}\n\tvoid ClampMax(const TYPE& v) {\n\t\tx = (x > v) ? v : x;\n\t\ty = (y > v) ? v : y;\n\t\tz = (z > v) ? v : z;\n\t\tw = (w > v) ? v : w;\n\t}\n\tvoid Abs() {\n\t\tx = cyAbs(x);\n\t\ty = cyAbs(y);\n\t\tz = cyAbs(z);\n\t\tw = cyAbs(w);\n\t}//!< Converts all negative components to positive values\n\n\t//!@name Unary operators\n\tPoint4 operator-() const {\n\t\tPoint4 r;\n\t\tr.x = -x;\n\t\tr.y = -y;\n\t\tr.z = -z;\n\t\tr.w = -w;\n\t\treturn r;\n\t}\n\n\t//!@name Binary operators\n\tPoint4 operator+(const Point4& p) const {\n\t\tPoint4 r;\n\t\tr.x = x + p.x;\n\t\tr.y = y + p.y;\n\t\tr.z = z + p.z;\n\t\tr.w = w + p.w;\n\t\treturn r;\n\t}\n\tPoint4 operator-(const Point4& p) const {\n\t\tPoint4 r;\n\t\tr.x = x - p.x;\n\t\tr.y = y - p.y;\n\t\tr.z = z - p.z;\n\t\tr.w = w - p.w;\n\t\treturn r;\n\t}\n\tPoint4 operator*(const Point4& p) const {\n\t\tPoint4 r;\n\t\tr.x = x * p.x;\n\t\tr.y = y * p.y;\n\t\tr.z = z * p.z;\n\t\tr.w = w * p.w;\n\t\treturn r;\n\t}\n\tPoint4 operator/(const Point4& p) const {\n\t\tPoint4 r;\n\t\tr.x = x / p.x;\n\t\tr.y = y / p.y;\n\t\tr.z = z / p.z;\n\t\tr.w = w / p.w;\n\t\treturn r;\n\t}\n\tPoint4 operator+(const TYPE& v) const {\n\t\tPoint4 r;\n\t\tr.x = x + v;\n\t\tr.y = y + v;\n\t\tr.z = z + v;\n\t\tr.w = w + v;\n\t\treturn r;\n\t}\n\tPoint4 operator-(const TYPE& v) const {\n\t\tPoint4 r;\n\t\tr.x = x - v;\n\t\tr.y = y - v;\n\t\tr.z = z - v;\n\t\tr.w = w - v;\n\t\treturn r;\n\t}\n\tPoint4 operator*(const TYPE& v) const {\n\t\tPoint4 r;\n\t\tr.x = x * v;\n\t\tr.y = y * v;\n\t\tr.z = z * v;\n\t\tr.w = w * v;\n\t\treturn r;\n\t}\n\tPoint4 operator/(const TYPE& v) const {\n\t\tPoint4 r;\n\t\tr.x = x / v;\n\t\tr.y = y / v;\n\t\tr.z = z / v;\n\t\tr.w = w / v;\n\t\treturn r;\n\t}\n\n\t//!@name Assignment operators\n\tconst Point4& operator=(const Point4& p) {\n\t\tx = p.x;\n\t\ty = p.y;\n\t\tz = p.z;\n\t\tw = p.w;\n\t\treturn *this;\n\t}\n\tconst Point4& operator+=(const Point4& p) {\n\t\tx += p.x;\n\t\ty += p.y;\n\t\tz += p.z;\n\t\tw += p.w;\n\t\treturn *this;\n\t}\n\tconst Point4& operator-=(const Point4& p) {\n\t\tx -= p.x;\n\t\ty -= p.y;\n\t\tz -= p.z;\n\t\tw -= p.w;\n\t\treturn *this;\n\t}\n\tconst Point4& operator*=(const Point4& p) {\n\t\tx *= p.x;\n\t\ty *= p.y;\n\t\tz *= p.z;\n\t\tw *= p.w;\n\t\treturn *this;\n\t}\n\tconst Point4& operator/=(const Point4& p) {\n\t\tx /= p.x;\n\t\ty /= p.y;\n\t\tz /= p.z;\n\t\tw /= p.w;\n\t\treturn *this;\n\t}\n\tconst Point4& operator+=(const TYPE& v) {\n\t\tx += v;\n\t\ty += v;\n\t\tz += v;\n\t\tw += v;\n\t\treturn *this;\n\t}\n\tconst Point4& operator-=(const TYPE& v) {\n\t\tx -= v;\n\t\ty -= v;\n\t\tz -= v;\n\t\tw -= v;\n\t\treturn *this;\n\t}\n\tconst Point4& operator*=(const TYPE& v) {\n\t\tx *= v;\n\t\ty *= v;\n\t\tz *= v;\n\t\tw *= v;\n\t\treturn *this;\n\t}\n\tconst Point4& operator/=(const TYPE& v) {\n\t\tx /= v;\n\t\ty /= v;\n\t\tz /= v;\n\t\tw /= v;\n\t\treturn *this;\n\t}\n\n\t//!@name Test operators\n\tbool operator==(const Point4& p) const {\n\t\treturn x == p.x && y == p.y && z == p.z && w == p.w;\n\t}\n\tbool operator!=(const Point4& p) const {\n\t\treturn x != p.x && y != p.y && z != p.z && w != p.w;\n\t}\n\n\t//!@name Access operators\n\tTYPE& operator[](int i) {\n\t\treturn Element(i);\n\t}\n\tconst TYPE& operator[](int i) const {\n\t\treturn Element(i);\n\t}\n\tTYPE& Element(int i) {\n\t\treturn (&x)[i];\n\t}\n\tconst TYPE& Element(int i) const {\n\t\treturn (&x)[i];\n\t}\n\tTYPE* Data() {\n\t\treturn &x;\n\t}\n\tconst TYPE* Data() const {\n\t\treturn &x;\n\t}\n\n\t//!@name Dot product\n\tTYPE Dot(const Point4& p) const {\n\t\tPoint4 r = operator*(p);\n\t\treturn r.Sum();\n\t}//!< Dot product\n\tTYPE operator%(const Point4& p) const {\n\t\treturn Dot(p);\n\t}//!< Dot product\n\n\t//!@name Conversion Methods\n\tPoint2 XY() const {\n\t\treturn Point2(*this);\n\t}\n\tPoint3 XYZ() const {\n\t\treturn Point3(*this);\n\t}\n\tPoint3 GetNonHomogeneous() const {\n\t\treturn Point3(*this) / w;\n\t}\n};\n\n//-------------------------------------------------------------------------------\n\n// Definitions of the conversion constructors\ntemplate\nPoint::Point(const Point2& p) {\n\tif(N <= 2) {\n\t\tCY_MEMCOPY(TYPE, data, &p.x, N);\n\t} else {\n\t\tCY_MEMCOPY(TYPE, data, &p.x, 2);\n\t\tCY_MEMCLEAR(TYPE, data, N - 2);\n\t}\n}\ntemplate\nPoint::Point(const Point3& p) {\n\tif(N <= 3) {\n\t\tCY_MEMCOPY(TYPE, data, &p.x, N);\n\t} else {\n\t\tCY_MEMCOPY(TYPE, data, &p.x, 3);\n\t\tCY_MEMCLEAR(TYPE, data, N - 3);\n\t}\n}\ntemplate\nPoint::Point(const Point4& p) {\n\tif(N <= 4) {\n\t\tCY_MEMCOPY(TYPE, data, &p.x, N);\n\t} else {\n\t\tCY_MEMCOPY(TYPE, data, &p.x, 4);\n\t\tCY_MEMCLEAR(TYPE, data, N - 4);\n\t}\n}\ntemplate\ntemplate\nPoint::Point(const Point2& p) {\n\tif(N <= 2) {\n\t\tCY_MEMCONVERT(TYPE, data, &p.x, N);\n\t} else {\n\t\tCY_MEMCONVERT(TYPE, data, &p.x, 2);\n\t\tCY_MEMCLEAR(TYPE, data, N - 2);\n\t}\n}\ntemplate\ntemplate\nPoint::Point(const Point3& p) {\n\tif(N <= 3) {\n\t\tCY_MEMCONVERT(TYPE, data, &p.x, N);\n\t} else {\n\t\tCY_MEMCONVERT(TYPE, data, &p.x, 3);\n\t\tCY_MEMCLEAR(TYPE, data, N - 3);\n\t}\n}\ntemplate\ntemplate\nPoint::Point(const Point4& p) {\n\tif(N <= 4) {\n\t\tCY_MEMCONVERT(TYPE, data, &p.x, N);\n\t} else {\n\t\tCY_MEMCONVERT(TYPE, data, &p.x, 4);\n\t\tCY_MEMCLEAR(TYPE, data, N - 4);\n\t}\n}\ntemplate\nPoint2::Point2(const Point3& p)\n\t: x(p.x)\n\t, y(p.y) {}\ntemplate\nPoint2::Point2(const Point4& p)\n\t: x(p.x)\n\t, y(p.y) {}\ntemplate\nPoint3::Point3(const Point4& p)\n\t: x(p.x)\n\t, y(p.y)\n\t, z(p.z) {}\ntemplate\ntemplate\nPoint2::Point2(const Point3& p)\n\t: x(TYPE(p.x))\n\t, y(TYPE(p.y)) {}\ntemplate\ntemplate\nPoint2::Point2(const Point4& p)\n\t: x(TYPE(p.x))\n\t, y(TYPE(p.y)) {}\ntemplate\ntemplate\nPoint3::Point3(const Point4& p)\n\t: x(TYPE(p.x))\n\t, y(TYPE(p.y))\n\t, z(TYPE(p.z)) {}\n\n//-------------------------------------------------------------------------------\n\ntypedef Point2 Point2f;//!< 2D point (vector) class with float type elements\ntypedef Point3 Point3f;//!< 3D point (vector) class with float type elements\ntypedef Point4 Point4f;//!< 4D point (vector) class with float type elements\n\ntypedef Point2 Point2d;//!< 2D point (vector) class with double type elements\ntypedef Point3 Point3d;//!< 3D point (vector) class with double type elements\ntypedef Point4 Point4d;//!< 4D point (vector) class with double type elements\n\n//-------------------------------------------------------------------------------\n}// namespace cy\n//-------------------------------------------------------------------------------\n\ntypedef cy::Point2f cyPoint2f;//!< 2D point (vector) class with float type elements\ntypedef cy::Point3f cyPoint3f;//!< 3D point (vector) class with float type elements\ntypedef cy::Point4f cyPoint4f;//!< 4D point (vector) class with float type elements\n\ntypedef cy::Point2d cyPoint2d;//!< 2D point (vector) class with double type elements\ntypedef cy::Point3d cyPoint3d;//!< 3D point (vector) class with double type elements\ntypedef cy::Point4d cyPoint4d;//!< 4D point (vector) class with double type elements\n\n//-------------------------------------------------------------------------------\n\n#endif\n" }, { "path": "Library/MnSystem/IO/PoissonDisk/cyPointCloud.h", "content": "// cyCodeBase by Cem Yuksel\n// [www.cemyuksel.com]\n//-------------------------------------------------------------------------------\n//! \\file cyPointCloud.h\n//! \\author Cem Yuksel\n//!\n//! \\brief Point cloud using a k-d tree\n//!\n//! This file includes a class that keeps a point cloud as a k-d tree\n//! for quickly finding n-nearest points to a given location.\n//!\n//-------------------------------------------------------------------------------\n//\n// Copyright (c) 2016, Cem Yuksel \n// All rights reserved.\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n//\n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n//\n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\n// SOFTWARE.\n//\n//-------------------------------------------------------------------------------\n\n#ifndef _CY_POINT_CLOUD_H_INCLUDED_\n#define _CY_POINT_CLOUD_H_INCLUDED_\n\n//-------------------------------------------------------------------------------\n\n#ifdef max\n#\tdefine _CY_POP_MACRO_max\n#\tpragma push_macro(\"max\")\n#\tundef max\n#endif\n\n//-------------------------------------------------------------------------------\n\n#include \n#include \n\n#include \n\n//-------------------------------------------------------------------------------\nnamespace cy {\n//-------------------------------------------------------------------------------\n\n//! A point cloud class that uses a k-d tree for storing points.\n//!\n//! The GetPoints and GetClosest methods return the neighboring points to a\n//! given location.\n\ntemplate\nclass PointCloud {\n public:\n\t/////////////////////////////////////////////////////////////////////////////////\n\t//!@name Constructors and Destructor\n\n\tPointCloud()\n\t\t: points(nullptr)\n\t\t, pointCount(0) {}\n\tPointCloud(SIZE_TYPE numPts, const PointType* pts, const SIZE_TYPE* customIndices = nullptr)\n\t\t: points(nullptr)\n\t\t, pointCount(0) {\n\t\tBuild(numPts, pts, customIndices);\n\t}\n\t~PointCloud() {\n\t\tdelete[] points;\n\t}\n\n\t/////////////////////////////////////////////////////////////////////////////////\n\t//!@ Access to internal data\n\n\tSIZE_TYPE GetPointCount() const {\n\t\treturn pointCount - 1;\n\t}//!< Returns the point count\n\tconst PointType& GetPoint(SIZE_TYPE i) const {\n\t\treturn points[i + 1].Pos();\n\t}//!< Returns the point at position i\n\tSIZE_TYPE GetPointIndex(SIZE_TYPE i) const {\n\t\treturn points[i + 1].Index();\n\t}//!< Returns the index of the point at position i\n\n\t/////////////////////////////////////////////////////////////////////////////////\n\t//!@ Initialization\n\n\t//! Builds a k-d tree for the given points.\n\t//! The point locations are stored internally, along with the indices to the\n\t//! given array.\n\tvoid Build(SIZE_TYPE numPts, const PointType* pts, const SIZE_TYPE* customIndices = nullptr) {\n\t\tif(points)\n\t\t\tdelete[] points;\n\t\tpointCount = numPts;\n\t\tif(pointCount == 0) {\n\t\t\tpoints = nullptr;\n\t\t\treturn;\n\t\t}\n\t\tpoints\t\t\t = new PointData[pointCount + 1];\n\t\tSIZE_TYPE* order = new SIZE_TYPE[pointCount];\n\t\tfor(SIZE_TYPE i = 0; i < pointCount; i++)\n\t\t\torder[i] = i;\n\t\tBuildKDTree(pts, customIndices, order, 1, 0, pointCount);\n\t\tdelete[] order;\n\t}\n\n\t/////////////////////////////////////////////////////////////////////////////////\n\t//!@ General search methods\n\n\t//! Returns all points to the given position within the given radius.\n\t//! Calls the given pointFound function for each point found.\n\t//!\n\t//! The given pointFound function can reduce the radiusSquared value.\n\t//! However, increasing the radiusSquared value can have unpredictable\n\t//! results. The callback function must be in the following form:\n\t//!\n\t//! void _CALLBACK(SIZE_TYPE index, const PointType &p, FType distanceSquared,\n\t//! FType &radiusSquared)\n\ttemplate\n\tvoid GetPoints(const PointType& position, FType radius, _CALLBACK pointFound) {\n\t\tSIZE_TYPE internalNodes = (pointCount + 1) >> 1;\n\t\tSIZE_TYPE stack[60];// deep enough for 2^30 points\n\t\tint stackPos = 0;\n\t\tstack[0]\t = 1;// root node\n\t\tFType dist2\t = radius * radius;\n\t\twhile(stackPos >= 0) {\n\t\t\tSIZE_TYPE ix\t\t= stack[stackPos--];\n\t\t\tconst PointData* p\t= &points[ix];\n\t\t\tconst PointType pos = p->Pos();\n\t\t\tif(ix < internalNodes) {\n\t\t\t\tint axis = p->Plane();\n\t\t\t\tFType d\t = position[axis] - pos[axis];\n\t\t\t\tif(d > 0) {// if dist1 is positive search right child first\n\t\t\t\t\tstack[++stackPos] = 2 * ix + 1;\n\t\t\t\t\tif(d * d < dist2)\n\t\t\t\t\t\tstack[++stackPos] = 2 * ix;\n\t\t\t\t} else {// dist1 is negative, search left child first\n\t\t\t\t\tstack[++stackPos] = 2 * ix;\n\t\t\t\t\tif(d * d < dist2)\n\t\t\t\t\t\tstack[++stackPos] = 2 * ix + 1;\n\t\t\t\t}\n\t\t\t}\n\t\t\tFType d2 = (pos - position).LengthSquared();\n\t\t\tif(d2 < dist2)\n\t\t\t\tpointFound(p->Index(), pos, d2, dist2);\n\t\t}\n\t\tif((pointCount & SIZE_TYPE(1)) == 0) {\n\t\t\tconst PointData* p = &points[pointCount];\n\t\t\tFType d2\t\t = (p->Pos() - position).LengthSquared();\n\t\t\tif(d2 < dist2)\n\t\t\t\tpointFound(p->Index(), p->Pos(), d2, dist2);\n\t\t}\n\t}\n\n\t//! Used by one of the PointCloud::GetPoints() methods.\n\t//!\n\t//! Keeps the point index, position, and distance squared to a given search\n\t//! position. Used by one of the GetPoints methods.\n\tstruct PointInfo {\n\t\tSIZE_TYPE index;\t //!< The index of the point\n\t\tPointType pos;\t\t //!< The position of the point\n\t\tFType distanceSquared;//!< Squared distance from the search position\n\t\tbool operator<(const PointInfo& b) const {\n\t\t\treturn distanceSquared < b.distanceSquared;\n\t\t}//!< Comparison operator\n\t};\n\n\t//! Returns the closest points to the given position within the given radius.\n\t//! It returns the number of points found.\n\tint GetPoints(const PointType& position, FType radius, SIZE_TYPE maxCount, PointInfo* closestPoints) {\n\t\tbool tooManyPoints = false;\n\t\tint pointsFound\t = 0;\n\t\tGetPoints(position, radius, [&](SIZE_TYPE i, const PointType& p, FType d2, FType& r2) {\n\t\t\tif(pointsFound == maxCount) {\n\t\t\t\tif(!tooManyPoints) {\n\t\t\t\t\tstd::make_heap(closestPoints, closestPoints + maxCount);\n\t\t\t\t}\n\t\t\t\tstd::pop_heap(closestPoints, closestPoints + maxCount);\n\t\t\t\tclosestPoints[maxCount - 1].index\t\t\t= i;\n\t\t\t\tclosestPoints[maxCount - 1].pos\t\t\t\t= p;\n\t\t\t\tclosestPoints[maxCount - 1].distanceSquared = d2;\n\t\t\t\tstd::push_heap(closestPoints, closestPoints + maxCount);\n\t\t\t\tr2 = closestPoints[0].distanceSquared;\n\t\t\t} else {\n\t\t\t\tclosestPoints[pointsFound].index\t\t = i;\n\t\t\t\tclosestPoints[pointsFound].pos\t\t\t = p;\n\t\t\t\tclosestPoints[pointsFound].distanceSquared = d2;\n\t\t\t\tpointsFound++;\n\t\t\t}\n\t\t});\n\t\treturn pointsFound;\n\t}\n\n\t//! Returns the closest points to the given position.\n\t//! It returns the number of points found.\n\tint GetPoints(const PointType& position, SIZE_TYPE maxCount, PointInfo* closestPoints) {\n\t\treturn GetPoints(position, std::numeric_limits::max(), maxCount, closestPoints);\n\t}\n\n\t/////////////////////////////////////////////////////////////////////////////////\n\t//!@name Closest point methods\n\n\t//! Returns the closest point to the given position within the given radius.\n\t//! It returns true, if a point is found.\n\tbool GetClosest(const PointType& position, FType radius, SIZE_TYPE& closestIndex, PointType& closestPosition, FType& closestDistanceSquared) {\n\t\tbool found = false;\n\t\tGetPoints(position, radius, [&](SIZE_TYPE i, const PointType& p, FType d2, FType& r2) {\n\t\t\tfound\t\t\t\t = true;\n\t\t\tclosestIndex\t\t = i;\n\t\t\tclosestPosition\t\t = p;\n\t\t\tclosestDistanceSquared = d2;\n\t\t\tr2\t\t\t\t\t = d2;\n\t\t});\n\t\treturn found;\n\t}\n\n\t//! Returns the closest point to the given position.\n\t//! It returns true, if a point is found.\n\tbool GetClosest(const PointType& position, SIZE_TYPE& closestIndex, PointType& closestPosition, FType& closestDistanceSquared) {\n\t\treturn GetClosest(position, std::numeric_limits::max(), closestIndex, closestPosition, closestDistanceSquared);\n\t}\n\n\t//! Returns the closest point index and position to the given position within\n\t//! the given index. It returns true, if a point is found.\n\tbool GetClosest(const PointType& position, FType radius, SIZE_TYPE& closestIndex, PointType& closestPosition) {\n\t\tFType closestDistanceSquared;\n\t\treturn GetClosest(position, radius, closestIndex, closestPosition, closestDistanceSquared);\n\t}\n\n\t//! Returns the closest point index and position to the given position.\n\t//! It returns true, if a point is found.\n\tbool GetClosest(const PointType& position, SIZE_TYPE& closestIndex, PointType& closestPosition) {\n\t\tFType closestDistanceSquared;\n\t\treturn GetClosest(position, closestIndex, closestPosition, closestDistanceSquared);\n\t}\n\n\t//! Returns the closest point index to the given position within the given\n\t//! radius. It returns true, if a point is found.\n\tbool GetClosestIndex(const PointType& position, FType radius, SIZE_TYPE& closestIndex) {\n\t\tFType closestDistanceSquared;\n\t\tPointType closestPosition;\n\t\treturn GetClosest(position, radius, closestIndex, closestPosition, closestDistanceSquared);\n\t}\n\n\t//! Returns the closest point index to the given position.\n\t//! It returns true, if a point is found.\n\tbool GetClosestIndex(const PointType& position, SIZE_TYPE& closestIndex) {\n\t\tFType closestDistanceSquared;\n\t\tPointType closestPosition;\n\t\treturn GetClosest(position, closestIndex, closestPosition, closestDistanceSquared);\n\t}\n\n\t//! Returns the closest point position to the given position within the given\n\t//! radius. It returns true, if a point is found.\n\tbool GetClosestPosition(const PointType& position, FType radius, PointType& closestPosition) {\n\t\tSIZE_TYPE closestIndex;\n\t\tFType closestDistanceSquared;\n\t\treturn GetClosest(position, radius, closestIndex, closestPosition, closestDistanceSquared);\n\t}\n\n\t//! Returns the closest point position to the given position.\n\t//! It returns true, if a point is found.\n\tbool GetClosestPosition(const PointType& position, PointType& closestPosition) {\n\t\tSIZE_TYPE closestIndex;\n\t\tFType closestDistanceSquared;\n\t\treturn GetClosest(position, closestIndex, closestPosition, closestDistanceSquared);\n\t}\n\n\t//! Returns the closest point distance squared to the given position within\n\t//! the given radius. It returns true, if a point is found.\n\tbool GetClosestDistanceSquared(const PointType& position, FType radius, FType& closestDistanceSquared) {\n\t\tSIZE_TYPE closestIndex;\n\t\tPointType closestPosition;\n\t\treturn GetClosest(position, radius, closestIndex, closestPosition, closestDistanceSquared);\n\t}\n\n\t//! Returns the closest point distance squared to the given position.\n\t//! It returns true, if a point is found.\n\tbool GetClosestDistanceSquared(const PointType& position, FType& closestDistanceSquared) {\n\t\tSIZE_TYPE closestIndex;\n\t\tPointType closestPosition;\n\t\treturn GetClosest(position, closestIndex, closestPosition, closestDistanceSquared);\n\t}\n\n\t/////////////////////////////////////////////////////////////////////////////////\n\n private:\n\t/////////////////////////////////////////////////////////////////////////////////\n\t//!@name Internal Structures and Methods\n\n\tclass PointData {\n\t private:\n\t\tSIZE_TYPE\n\t\tindexAndSplitPlane;// first NBits bits indicates the splitting plane,\n\t\t\t\t\t\t // the rest of the bits store the point index.\n\t\tPointType p;\t // point position\n\n\t public:\n\t\tvoid Set(const PointType& pt, SIZE_TYPE index, uint32_t plane = 0) {\n\t\t\tp\t\t\t\t = pt;\n\t\t\tindexAndSplitPlane = (index << NBits()) | (plane & ((1 << NBits()) - 1));\n\t\t}\n\t\tint Plane() const {\n\t\t\treturn indexAndSplitPlane & ((1 << NBits()) - 1);\n\t\t}\n\t\tSIZE_TYPE Index() const {\n\t\t\treturn indexAndSplitPlane >> NBits();\n\t\t}\n\t\tconst PointType& Pos() const {\n\t\t\treturn p;\n\t\t}\n\n\t private:\n#if defined(__cpp_constexpr) || (defined(_MSC_VER) && _MSC_VER >= 1900)\n\t\tconstexpr int NBits(uint32_t v = DIMENSIONS) const {\n\t\t\treturn v < 2 ? v : 1 + NBits(v >> 1);\n\t\t}\n#else\n\t\tint NBits() const {\n\t\t\tint v = DIMENSIONS - 1, r, s;\n\t\t\tr\t = (v > 0xF) << 2;\n\t\t\tv >>= r;\n\t\t\ts = (v > 0x3) << 1;\n\t\t\tv >>= s;\n\t\t\tr |= s | (v >> 1);\n\t\t\treturn r + 1;\n\t\t}// Supports up to 256 dimensions\n#endif\n\t};\n\n\tPointData* points;\t // Keeps the points as a k-d tree.\n\tSIZE_TYPE pointCount;// Keeps the point count.\n\n\t// The main method for recursively building the k-d tree.\n\tvoid BuildKDTree(const PointType* pts, const SIZE_TYPE* indices, SIZE_TYPE* order, SIZE_TYPE kdIndex, SIZE_TYPE ixStart, SIZE_TYPE ixEnd) {\n\t\tSIZE_TYPE n = ixEnd - ixStart;\n\t\tif(n <= 1) {\n\t\t\tif(n > 0) {\n\t\t\t\tSIZE_TYPE ix = order[ixStart];\n\t\t\t\tif(indices)\n\t\t\t\t\tpoints[kdIndex].Set(pts[ix], indices[ix]);\n\t\t\t\telse\n\t\t\t\t\tpoints[kdIndex].Set(pts[ix], ix);\n\t\t\t}\n\t\t} else {\n\t\t\tint axis\t\t = SplitAxis(pts, order, ixStart, ixEnd);\n\t\t\tSIZE_TYPE leftSize = LeftSize(n);\n\t\t\tSIZE_TYPE ixMid\t = ixStart + leftSize;\n\t\t\tstd::nth_element(order + ixStart, order + ixMid, order + ixEnd, [&pts, axis](const int& a, const int& b) {\n\t\t\t\treturn pts[a][axis] < pts[b][axis];\n\t\t\t});\n\t\t\tSIZE_TYPE ix = order[ixMid];\n\t\t\tif(indices)\n\t\t\t\tpoints[kdIndex].Set(pts[ix], indices[ix], axis);\n\t\t\telse\n\t\t\t\tpoints[kdIndex].Set(pts[ix], ix, axis);\n\t\t\tBuildKDTree(pts, indices, order, kdIndex * 2, ixStart, ixMid);\n\t\t\tBuildKDTree(pts, indices, order, kdIndex * 2 + 1, ixMid + 1, ixEnd);\n\t\t}\n\t}\n\n\t// Returns the total number of nodes on the left sub-tree of a complete k-d\n\t// tree of size n.\n\tSIZE_TYPE LeftSize(SIZE_TYPE n) {\n\t\tSIZE_TYPE f = n;// Size of the full tree\n\t\tfor(SIZE_TYPE s = 1; s < (SIZE_TYPE) (8 * sizeof(SIZE_TYPE)); s *= 2)\n\t\t\tf |= f >> s;\n\t\tSIZE_TYPE l = f >> 1;// Size of the full left child\n\t\tSIZE_TYPE r = l >> 1;// Size of the full right child without leaf nodes\n\t\treturn (l + r + 1 <= n) ? l : n - r - 1;\n\t}\n\n\t// Returns axis with the largest span, used as the splitting axis for building\n\t// the k-d tree\n\tint SplitAxis(const PointType* pts, SIZE_TYPE* indices, SIZE_TYPE ixStart, SIZE_TYPE ixEnd) {\n\t\tPointType box_min = pts[indices[ixStart]];\n\t\tPointType box_max = box_min;\n\t\tfor(SIZE_TYPE i = ixStart + 1; i < ixEnd; i++) {\n\t\t\tPointType p = pts[indices[i]];\n\t\t\tfor(SIZE_TYPE d = 0; d < (SIZE_TYPE) DIMENSIONS; d++) {\n\t\t\t\tif(box_min[d] > p[d])\n\t\t\t\t\tbox_min[d] = p[d];\n\t\t\t\tif(box_max[d] < p[d])\n\t\t\t\t\tbox_max[d] = p[d];\n\t\t\t}\n\t\t}\n\t\tint axis = 0;\n\t\t{\n\t\t\tFType axisSize = box_max[0] - box_min[0];\n\t\t\tfor(SIZE_TYPE d = 1; d < (SIZE_TYPE) DIMENSIONS; d++) {\n\t\t\t\tFType s = box_max[d] - box_min[d];\n\t\t\t\tif(axisSize < s) {\n\t\t\t\t\taxis\t = d;\n\t\t\t\t\taxisSize = s;\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\treturn axis;\n\t}\n\n\t/////////////////////////////////////////////////////////////////////////////////\n};\n\n//-------------------------------------------------------------------------------\n\n#ifdef _CY_POINT_H_INCLUDED_\ntemplate\n_CY_TEMPLATE_ALIAS(PointCloud2, (PointCloud, TYPE, 2>) );//!< A 2D point cloud using a k-d tree\ntemplate\n_CY_TEMPLATE_ALIAS(PointCloud3, (PointCloud, TYPE, 3>) );//!< A 3D point cloud using a k-d tree\ntemplate\n_CY_TEMPLATE_ALIAS(PointCloud4, (PointCloud, TYPE, 4>) );//!< A 4D point cloud using a k-d tree\n\ntypedef PointCloud PointCloud2f;//!< A 2D point cloud using a k-d tree with float type\n\t\t\t\t\t\t\t\t\t\t\t\t //!< elements\ntypedef PointCloud PointCloud3f;//!< A 3D point cloud using a k-d tree with float type\n\t\t\t\t\t\t\t\t\t\t\t\t //!< elements\ntypedef PointCloud PointCloud4f;//!< A 4D point cloud using a k-d tree with float type\n\t\t\t\t\t\t\t\t\t\t\t\t //!< elements\n\ntypedef PointCloud PointCloud2d;//!< A 2D point cloud using a k-d tree with double type\n\t\t\t\t\t\t\t\t\t\t\t\t\t//!< elements\ntypedef PointCloud PointCloud3d;//!< A 3D point cloud using a k-d tree with double type\n\t\t\t\t\t\t\t\t\t\t\t\t\t//!< elements\ntypedef PointCloud PointCloud4d;//!< A 4D point cloud using a k-d tree with double type\n\t\t\t\t\t\t\t\t\t\t\t\t\t//!< elements\n\ntemplate\n_CY_TEMPLATE_ALIAS(\n\tPointCloudN,\n\t(PointCloud<\n\t\tPoint,\n\t\tTYPE,\n\t\tDIMENSIONS>)\n);\t//!< A multi-dimensional point\n\t//!< cloud using a k-d tree\ntemplate\n_CY_TEMPLATE_ALIAS(PointCloudNf, (PointCloudN) );//!< A multi-dimensional point cloud\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t//!< using a k-d tree with single\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t//!< precision (float)\ntemplate\n_CY_TEMPLATE_ALIAS(PointCloudNd, (PointCloudN) );//!< A multi-dimensional point cloud\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t //!< using a k-d tree with double\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t //!< precision (double)\n#endif\n\n//-------------------------------------------------------------------------------\n}// namespace cy\n//-------------------------------------------------------------------------------\n\n#ifdef _CY_POINT_H_INCLUDED_\ntemplate\n_CY_TEMPLATE_ALIAS(\n\tcyPointCloud2,\n\t(cy::PointCloud<\n\t\tcy::Point2,\n\t\tTYPE,\n\t\t2>)\n);//!< A 2D point cloud using a k-d tree\ntemplate\n_CY_TEMPLATE_ALIAS(\n\tcyPointCloud3,\n\t(cy::PointCloud<\n\t\tcy::Point3,\n\t\tTYPE,\n\t\t3>)\n);//!< A 3D point cloud using a k-d tree\ntemplate\n_CY_TEMPLATE_ALIAS(\n\tcyPointCloud4,\n\t(cy::PointCloud<\n\t\tcy::Point4,\n\t\tTYPE,\n\t\t4>)\n);//!< A 4D point cloud using a k-d tree\n\ntypedef cy::PointCloud cyPointCloud2f;//!< A 2D point cloud using a k-d tree with float type\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t //!< elements\ntypedef cy::PointCloud cyPointCloud3f;//!< A 3D point cloud using a k-d tree with float type\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t //!< elements\ntypedef cy::PointCloud cyPointCloud4f;//!< A 4D point cloud using a k-d tree with float type\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t //!< elements\n\ntypedef cy::PointCloud cyPointCloud2d;//!< A 2D point cloud using a k-d tree with double type\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t //!< elements\ntypedef cy::PointCloud cyPointCloud3d;//!< A 3D point cloud using a k-d tree with double type\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t //!< elements\ntypedef cy::PointCloud cyPointCloud4d;//!< A 4D point cloud using a k-d tree with double type\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t //!< elements\n\ntemplate\n_CY_TEMPLATE_ALIAS(\n\tcyPointCloudN,\n\t(cy::PointCloud<\n\t\tcy::Point,\n\t\tTYPE,\n\t\tDIMENSIONS>)\n);\t//!< A multi-dimensional point\n\t//!< cloud using a k-d tree\ntemplate\n_CY_TEMPLATE_ALIAS(cyPointCloudNf, (cyPointCloudN) );//!< A multi-dimensional point cloud\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t//!< using a k-d tree with float type\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t//!< elements\ntemplate\n_CY_TEMPLATE_ALIAS(cyPointCloudNd, (cyPointCloudN) );//!< A multi-dimensional point cloud\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t //!< using a k-d tree with double type\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t //!< elements\n#endif\n\n//-------------------------------------------------------------------------------\n\n#ifdef _CY_POP_MACRO_max\n#\tpragma pop_macro(\"max\")\n#\tundef _CY_POP_MACRO_max\n#endif\n\n//-------------------------------------------------------------------------------\n\n#endif\n" }, { "path": "Library/MnSystem/IO/PoissonDisk/cySampleElim.h", "content": "// cyCodeBase by Cem Yuksel\n// [www.cemyuksel.com]\n//-------------------------------------------------------------------------------\n//! \\file cySampleElim.h\n//! \\author Cem Yuksel\n//!\n//! \\brief Implementation of the weighted sample elimination method.\n//!\n//! This file includes an implementation of the weighted sample elimination\n//! method for generating Poisson disk sample sets.\n//!\n//! Blue noise (Poisson disk) sample sets produce high-quality sampling. They\n//! often lead to lower noise and better convergence with Monte Carlo sampling.\n//! They provide a uniform sample distribution over a sampling domain. Unlike\n//! regular random sampling, Poisson disk sample sets avoid placing any two\n//! samples too close together (determined by a Poisson disk radius).\n//!\n//! The weighted sample elimination method implemented in this file generates a\n//! subset of samples with blue noise (Poisson disk) characteristics from a given\n//! input sample set. The weighted sample elimination method is simple,\n//! computationally efficient, and suitable for any sampling domain. It produces\n//! high-quality blue noise sample sets with a relatively large average Poisson\n//! disk radius without the need for specifying a Poisson disk radius. It also\n//! allows progressive (adaptive) sampling and it is efficient for high-\n//! dimensional sampling. However, it does not guarantee maximal coverage.\n//!\n//! More details can be found in the original publication:\n//!\n//! Cem Yuksel. 2015. Sample Elimination for Generating Poisson Disk Sample Sets.\n//! Computer Graphics Forum 34, 2 (May 2015), 25-32.\n//! http://www.cemyuksel.com/research/sampleelimination/\n//!\n//-------------------------------------------------------------------------------\n//\n// Copyright (c) 2016, Cem Yuksel \n// All rights reserved.\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n//\n// The above copyright notice and this permission notice shall be included in all\n// copies or substantial portions of the Software.\n//\n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\n// SOFTWARE.\n//\n//-------------------------------------------------------------------------------\n\n#ifndef _CY_SAMPLE_ELIM_H_INCLUDED_\n#define _CY_SAMPLE_ELIM_H_INCLUDED_\n\n//-------------------------------------------------------------------------------\n\n#include \"cyCore.h\"\n#include \"cyHeap.h\"\n#include \"cyPointCloud.h\"\n\n//-------------------------------------------------------------------------------\nnamespace cy {\n//-------------------------------------------------------------------------------\n\n//! An implementation of the weighted sample elimination method.\n//!\n//! Cem Yuksel. 2015. Sample Elimination for Generating Poisson Disk Sample Sets.\n//! Computer Graphics Forum 34, 2 (May 2015), 25-32.\n//! http://www.cemyuksel.com/research/sampleelimination/\n//!\n//! This class keeps a number of parameters for the weighted sample elimination algorithm.\n//! The main algorithm is implemented in the Eliminate method.\n\ntemplate\nclass WeightedSampleElimination {\n public:\n\t//! The constructor sets the default parameters.\n\tWeightedSampleElimination() {\n\t\tfor(int d = 0; d < DIMENSIONS; d++) {\n\t\t\tboundsMin[d] = FType(0);\n\t\t\tboundsMax[d] = FType(1);\n\t\t}\n\t\talpha\t\t = FType(8);\n\t\tbeta\t\t = FType(0.65);\n\t\tgamma\t\t = FType(1.5);\n\t\ttiling\t\t = false;\n\t\tweightLimiting = true;\n\t}\n\n\t//! Tiling determines whether the generated samples are tile-able.\n\t//! Tiling is off by default, but it is a good idea to turn it on for box-shaped sampling domains.\n\t//! Note that when tiling is off, weighted sample elimination is less likely to eliminate samples\n\t//! near the boundaries of the sampling domain. If you turn on tiling, make sure to set the\n\t//! correct boundaries for the sampling domain.\n\tvoid SetTiling(bool on = true) {\n\t\ttiling = on;\n\t}\n\n\t//! Returns true if the tiling parameter is turned on.\n\tbool IsTiling() const {\n\t\treturn tiling;\n\t}\n\n\t//! Weight limiting is used by the default weight function and it is on by default.\n\t//! Using weight limiting typically leads to more pronounced blue noise characteristics;\n\t//! therefore, it is recommended. The beta parameter determines the amount of weight limiting.\n\t//! Setting the beta parameter to zero effectively turns off weight limiting.\n\tvoid SetWeightLimiting(bool on = true) {\n\t\tweightLimiting = on;\n\t}\n\n\t//! Returns true if weight limiting is turned on.\n\tbool IsWeightLimiting() const {\n\t\treturn weightLimiting;\n\t}\n\n\t//! Returns the minimum bounds of the sampling domain.\n\t//! The sampling domain boundaries are used for tiling and computing the maximum possible\n\t//! Poisson disk radius for the sampling domain. The default boundaries are between 0 and 1.\n\tconst PointType& GetBoundsMin() const {\n\t\treturn boundsMin;\n\t}\n\n\t//! Returns the maximum bounds of the sampling domain.\n\t//! The sampling domain boundaries are used for tiling and computing the maximum possible\n\t//! Poisson disk radius for the sampling domain. The default boundaries are between 0 and 1.\n\tconst PointType& GetBoundsMax() const {\n\t\treturn boundsMax;\n\t}\n\n\t//! Sets the minimum bounds of the sampling domain.\n\t//! The sampling domain boundaries are used for tiling and computing the maximum possible\n\t//! Poisson disk radius for the sampling domain. The default boundaries are between 0 and 1.\n\tvoid SetBoundsMin(const PointType& bmin) {\n\t\tboundsMin = bmin;\n\t}\n\n\t//! Sets the maximum bounds of the sampling domain.\n\t//! The sampling domain boundaries are used for tiling and computing the maximum possible\n\t//! Poisson disk radius for the sampling domain. The default boundaries are between 0 and 1.\n\tvoid SetBoundsMax(const PointType& bmax) {\n\t\tboundsMax = bmax;\n\t}\n\n\t//! Sets the alpha parameter that is used by the default weight function.\n\tvoid SetParamAlpha(FType a) {\n\t\talpha = a;\n\t}\n\n\t//! Returns the alpha parameter that is used by the default weight function.\n\tFType GetParamAlpha() const {\n\t\treturn alpha;\n\t}\n\n\t//! Sets the beta parameter that is used by weight limiting for the default weight function.\n\t//! Setting the beta parameter to zero effectively turns off weight limiting.\n\t//! If weight limiting is off, this parameter has no effect.\n\tvoid SetParamBeta(FType b) {\n\t\tbeta = b;\n\t}\n\n\t//! Returns the beta parameter that is used by weight limiting for the default weight function.\n\tFType GetParamBeta() const {\n\t\treturn beta;\n\t}\n\n\t//! Sets the gamma parameter that is used by weight limiting for the default weight function.\n\t//! The gamma parameter adjusts weight limiting based on the ratio of the input and output counts.\n\t//! If weight limiting is off, this parameter has no effect.\n\tvoid SetParamGamma(FType c) {\n\t\tgamma = c;\n\t}\n\n\t//! Returns the gamma parameter that is used by weight limiting for the default weight function.\n\tFType GetParamGamma() const {\n\t\treturn gamma;\n\t}\n\n\t//! This is the main method that uses weighted sample elimination for selecting a subset of samples\n\t//! with blue noise (Poisson disk) characteristics from a given input sample set (inputPoints).\n\t//! The selected samples are copied to outputPoints. The output size must be smaller than the input size.\n\t//!\n\t//! If the progressive parameter is true, the output sample points are ordered for progressive sampling,\n\t//! such that when the samples are introduced one by one in this order, each subset in the sequence\n\t//! exhibits blue noise characteristics.\n\t//!\n\t//! The d_max parameter defines radius within which the weight function is non-zero.\n\t//!\n\t//! The dimensions parameter specifies the dimensionality of the sampling domain. This parameter\n\t//! would typically be equal to the dimensionality of the sampling domain (specified by DIMENSIONS).\n\t//! However, smaller values can be used when sampling a low-dimensional manifold in a high-dimensional\n\t//! space, such as a surface in 3D.\n\t//!\n\t//! The weight function is the crucial component of weighted sample elimination. It computes the weight\n\t//! of a sample point based on the placement of its neighbors within d_max radius. The weight function\n\t//! must have the following form:\n\t//!\n\t//! FType weightFunction( const PointType &p0, const PointType &p1, FType dist2, FType d_max )\n\t//!\n\t//! The arguments p0 and p1 are the two neighboring points, dist2 is the square of the Euclidean distance\n\t//! between these two points, and d_max is the current radius for the weight function.\n\t//! Note that if the progressive parameter is on, the d_max value sent to the weight function can be\n\t//! different than the d_max value passed to this method.\n\ttemplate\n\tvoid Eliminate(const PointType* inputPoints, SIZE_TYPE inputSize, PointType* outputPoints, SIZE_TYPE outputSize, bool progressive, FType d_max, int dimensions, WeightFunction weightFunction) const {\n\t\tassert(outputSize < inputSize);\n\t\tassert(dimensions <= DIMENSIONS && dimensions >= 2);\n\t\tif(d_max <= FType(0))\n\t\t\td_max = 2 * GetMaxPoissonDiskRadius(dimensions, outputSize);\n\t\tDoEliminate(inputPoints, inputSize, outputPoints, outputSize, d_max, weightFunction, false);\n\t\tif(progressive) {\n\t\t\tstd::vector tmpPoints(outputSize);\n\t\t\tPointType* inPts = outputPoints;\n\t\t\tPointType* outPts = tmpPoints.data();\n\t\t\tSIZE_TYPE inSize = outputSize;\n\t\t\tSIZE_TYPE outSize = 0;\n\t\t\twhile(inSize >= 3) {\n\t\t\t\toutSize = inSize / 2;\n\t\t\t\td_max *= ProgressiveRadiusMultiplier(dimensions);\n\t\t\t\tDoEliminate(inPts, inSize, outPts, outSize, d_max, weightFunction, true);\n\t\t\t\tif(outPts != outputPoints)\n\t\t\t\t\tCY_MEMCOPY(PointType, outputPoints + outSize, outPts + outSize, inSize - outSize);\n\t\t\t\tPointType* tmpPts = inPts;\n\t\t\t\tinPts\t\t\t = outPts;\n\t\t\t\toutPts\t\t\t = tmpPts;\n\t\t\t\tinSize\t\t\t = outSize;\n\t\t\t}\n\t\t\tif(inPts != outputPoints)\n\t\t\t\tCY_MEMCOPY(PointType, outputPoints, inPts, outSize);\n\t\t}\n\t}\n\n\t//! This is the main method that uses weighted sample elimination for selecting a subset of samples\n\t//! with blue noise (Poisson disk) characteristics from a given input sample set (inputPoints).\n\t//! The selected samples are copied to outputPoints. The output size must be smaller than the input size.\n\t//! This method uses the default weight function.\n\t//!\n\t//! If the progressive parameter is true, the output sample points are ordered for progressive sampling,\n\t//! such that when the samples are introduced one by one in this order, each subset in the sequence\n\t//! exhibits blue noise characteristics.\n\t//!\n\t//! The d_max parameter defines radius within which the weight function is non-zero. If this parameter\n\t//! is zero (or negative), it is automatically computed using the sampling dimensions and the size of\n\t//! the output set.\n\t//!\n\t//! The dimensions parameter specifies the dimensionality of the sampling domain. This parameter\n\t//! would typically be equal to the dimensionality of the sampling domain (specified by DIMENSIONS).\n\t//! However, smaller values can be used when sampling a low-dimensional manifold in a high-dimensional\n\t//! space, such as a surface in 3D.\n\tvoid Eliminate(const PointType* inputPoints, SIZE_TYPE inputSize, PointType* outputPoints, SIZE_TYPE outputSize, bool progressive = false, FType d_max = FType(0), int dimensions = DIMENSIONS) const {\n\t\tif(d_max <= FType(0))\n\t\t\td_max = 2 * GetMaxPoissonDiskRadius(dimensions, outputSize);\n\n\t\tstd::cout << d_max << std::endl;\n\n\t\tFType alpha = this->alpha;\n\t\tif(weightLimiting) {\n\t\t\tFType d_min = d_max * GetWeightLimitFraction(inputSize, outputSize);\n\t\t\tstd::cout << d_min << std::endl;\n\t\t\tEliminate(inputPoints, inputSize, outputPoints, outputSize, progressive, d_max, dimensions, [d_min, alpha](const PointType&, const PointType&, FType d2, FType d_max) {\n\t\t\t\tFType d = cySqrt(d2);\n\t\t\t\tif(d < d_min)\n\t\t\t\t\td = d_min;\n\t\t\t\treturn cyPow(FType(1) - d / d_max, alpha);\n\t\t\t});\n\t\t} else {\n\t\t\tEliminate(inputPoints, inputSize, outputPoints, outputSize, progressive, d_max, dimensions, [alpha](const PointType&, const PointType&, FType d2, FType d_max) {\n\t\t\t\tFType d = cySqrt(d2);\n\t\t\t\treturn cyPow(FType(1) - d / d_max, alpha);\n\t\t\t});\n\t\t}\n\t}\n\n\t//! Returns the maximum possible Poisson disk radius in the given dimensions for the given sampleCount\n\t//! to spread over the given domainSize. If the domainSize argument is zero or negative, it is computed\n\t//! as the area or N-dimensional volume of the box defined by the minimum and maximum bounds.\n\t//! This method is used for the default weight function.\n\tFType GetMaxPoissonDiskRadius(int dimensions, SIZE_TYPE sampleCount, FType domainSize = 0) const {\n\t\tassert(dimensions >= 2);\n\t\tif(domainSize <= FType(0)) {\n\t\t\tdomainSize = boundsMax[0] - boundsMin[0];\n\t\t\tfor(int d = 1; d < DIMENSIONS; d++) {\n\t\t\t\tdomainSize *= boundsMax[0] - boundsMin[0];\n\t\t\t}\n\t\t}\n\t\tFType sampleArea = domainSize / (FType) sampleCount;\n\t\tFType r_max;\n\t\tswitch(dimensions) {\n\t\t\tcase 2:\n\t\t\t\tr_max = cySqrt(sampleArea / (FType(2) * cySqrt(FType(3))));\n\t\t\t\tbreak;\n\t\t\tcase 3:\n\t\t\t\tr_max = cyPow(sampleArea / (FType(4) * cySqrt(FType(2))), FType(1) / FType(3));\n\t\t\t\tbreak;\n\t\t\tdefault:\n\t\t\t\tFType c;\n\t\t\t\tint d_start;\n\t\t\t\tif((dimensions & 1)) {\n\t\t\t\t\tc\t\t= FType(2);\n\t\t\t\t\td_start = 3;\n\t\t\t\t} else {\n\t\t\t\t\tc\t\t= cyPi();\n\t\t\t\t\td_start = 4;\n\t\t\t\t}\n\t\t\t\tfor(int d = d_start; d <= dimensions; d += 2)\n\t\t\t\t\tc *= FType(2) * cyPi() / FType(d);\n\t\t\t\tr_max = cyPow(sampleArea / c, FType(1) / FType(dimensions));\n\t\t\t\tbreak;\n\t\t}\n\t\treturn r_max;\n\t}\n\n private:\n\tPointType boundsMin;\t // The minimum bounds of the sampling domain.\n\tPointType boundsMax;\t // The maximum bounds of the sampling domain.\n\tFType alpha, beta, gamma;// Parameters of the default weight function.\n\tbool weightLimiting;\t // Specifies whether weight limiting is used with the default weight function.\n\tbool tiling;\t\t\t // Specifies whether the sampling domain is tiled.\n\n\t// Reflects a point near the bounds of the sampling domain off of all domain bounds for tiling.\n\ttemplate\n\tvoid TilePoint(SIZE_TYPE index, const PointType& point, FType d_max, OPERATION operation, int dim = 0) const {\n\t\tfor(int d = dim; d < DIMENSIONS; d++) {\n\t\t\tif(boundsMax[d] - point[d] < d_max) {\n\t\t\t\tPointType p = point;\n\t\t\t\tp[d] -= boundsMax[d] - boundsMin[d];\n\t\t\t\toperation(index, p);\n\t\t\t\tTilePoint(index, p, d_max, operation, d + 1);\n\t\t\t}\n\t\t\tif(point[d] - boundsMin[d] < d_max) {\n\t\t\t\tPointType p = point;\n\t\t\t\tp[d] += boundsMax[d] - boundsMin[d];\n\t\t\t\toperation(index, p);\n\t\t\t\tTilePoint(index, p, d_max, operation, d + 1);\n\t\t\t}\n\t\t}\n\t}\n\n\t// This is the method that performs weighted sample elimination.\n\ttemplate\n\tvoid DoEliminate(const PointType* inputPoints, SIZE_TYPE inputSize, PointType* outputPoints, SIZE_TYPE outputSize, FType d_max, WeightFunction weightFunction, bool copyEliminated) const {\n\t\t// Build a k-d tree for samples\n\t\tPointCloud kdtree;\n\t\tif(tiling) {\n\t\t\tstd::vector point(inputPoints, inputPoints + inputSize);\n\t\t\tstd::vector index(inputSize);\n\t\t\tfor(SIZE_TYPE i = 0; i < inputSize; i++)\n\t\t\t\tindex[i] = i;\n\t\t\tauto AppendPoint = [&](SIZE_TYPE ix, const PointType& pt) {\n\t\t\t\tpoint.push_back(pt);\n\t\t\t\tindex.push_back(ix);\n\t\t\t};\n\t\t\tfor(SIZE_TYPE i = 0; i < inputSize; i++)\n\t\t\t\tTilePoint(i, inputPoints[i], d_max, AppendPoint);\n\t\t\tkdtree.Build(point.size(), point.data(), index.data());\n\t\t} else {\n\t\t\tkdtree.Build(inputSize, inputPoints);\n\t\t}\n\n\t\t// Assign weights to each sample\n\t\tstd::vector w(inputSize, FType(0));\n\t\tauto AddWeights = [&](SIZE_TYPE index, const PointType& point) {\n\t\t\tkdtree.GetPoints(point, d_max, [&weightFunction, d_max, &w, index, &point, &inputSize](SIZE_TYPE i, const PointType& p, FType d2, FType&) {\n\t\t\t\tif(i >= inputSize)\n\t\t\t\t\treturn;\n\t\t\t\tif(i != index)\n\t\t\t\t\tw[index] += weightFunction(point, p, d2, d_max);\n\t\t\t});\n\t\t};\n\t\tfor(SIZE_TYPE i = 0; i < inputSize; i++)\n\t\t\tAddWeights(i, inputPoints[i]);\n\n\t\t// Build a heap for the samples using their weights\n\t\tHeap heap;\n\t\theap.SetDataPointer(w.data(), inputSize);\n\t\theap.Build();\n\n\t\t// While the number of samples is greater than desired\n\t\tauto RemoveWeights = [&](SIZE_TYPE index, const PointType& point) {\n\t\t\tkdtree.GetPoints(point, d_max, [&weightFunction, d_max, &w, index, &point, &heap, &inputSize](SIZE_TYPE i, const PointType& p, FType d2, FType&) {\n\t\t\t\tif(i >= inputSize)\n\t\t\t\t\treturn;\n\t\t\t\tif(i != index) {\n\t\t\t\t\tw[i] -= weightFunction(point, p, d2, d_max);\n\t\t\t\t\theap.MoveItemDown(i);\n\t\t\t\t}\n\t\t\t});\n\t\t};\n\t\tSIZE_TYPE sampleSize = inputSize;\n\t\twhile(sampleSize > outputSize) {\n\t\t\t// Pull the top sample from heap\n\t\t\tSIZE_TYPE i = heap.GetTopItemID();\n\t\t\theap.Pop();\n\t\t\t// For each sample around it, remove its weight contribution and update the heap\n\t\t\tRemoveWeights(i, inputPoints[i]);\n\t\t\tsampleSize--;\n\t\t}\n\n\t\t// Copy the samples to the output array\n\t\tSIZE_TYPE targetSize = copyEliminated ? inputSize : outputSize;\n\t\tfor(SIZE_TYPE i = 0; i < targetSize; i++) {\n\t\t\toutputPoints[i] = inputPoints[heap.GetIDFromHeap(i)];\n\t\t}\n\t}\n\n\t// Returns the change in weight function radius using half of the number of samples. It is used for progressive sampling.\n\tfloat ProgressiveRadiusMultiplier(int dimensions) const {\n\t\treturn dimensions == 2 ? cySqrt(FType(2)) : cyPow(FType(2), FType(1) / FType(dimensions));\n\t}\n\n\t// Returns the minimum radius fraction used by the default weight function.\n\tFType GetWeightLimitFraction(SIZE_TYPE inputSize, SIZE_TYPE outputSize) const {\n\t\tFType ratio = FType(outputSize) / FType(inputSize);\n\t\treturn (1 - cyPow(ratio, gamma)) * beta;\n\t}\n};\n\n//-------------------------------------------------------------------------------\n}// namespace cy\n//-------------------------------------------------------------------------------\n\n#endif\n" }, { "path": "Library/MnSystem/sourcelist.cmake", "content": "set(CudaSystemSrc\n\t${PROJECT_SOURCE_DIR}/Library/MnSystem/Cuda/Cuda.cu\n\t${PROJECT_SOURCE_DIR}/Library/MnSystem/Cuda/DeviceUtils.cu\n\t${PROJECT_SOURCE_DIR}/Library/MnSystem/Cuda/MemoryUtils.cu\n)" }, { "path": "Projects/CMakeLists.txt", "content": "# borrowed from taichi\nfile(GLOB children RELATIVE ${CMAKE_CURRENT_LIST_DIR} *)\n\nforeach(dir ${children})\n if(IS_DIRECTORY \"${CMAKE_CURRENT_LIST_DIR}/${dir}\")\n if (${dir} MATCHES \"^_\")\n message(\"Ignoring project ${dir}. (Starts with '_'.)\")\n else()\n if (EXISTS \"${CMAKE_CURRENT_LIST_DIR}/${dir}/CMakeLists.txt\")\n message(\"Adding project ${dir}:\")\n add_subdirectory(${dir})\n else()\n message(\"Ignoring project ${dir}. (No CMakeLists.txt.)\")\n endif()\n endif()\n endif()\n message(\"---------------------------------------------------------------\")\nendforeach()\n\nset(MN_PROJECT_LIBRARIES ${MN_PROJECT_LIBRARIES} PARENT_SCOPE)" }, { "path": "Projects/GMPM/CMakeLists.txt", "content": "if (CUDA_FOUND)\n\tadd_cuda_executable(gmpm)\n\t\n\ttarget_sources(gmpm\n\t\tPRIVATE gmpm.cu\n\t)\n\t\n\ttarget_link_libraries(gmpm\n\t\tPRIVATE mnio\n\t\t\t\t\tcxxopts\n\t\t\t\t\tspdlog\n\t\t\t\t\tfmt\n\t\t\t\t\trapidjson\n\t\t\t\t\trange-v3\n\t)\n\n\t#Add headers as system headers\n\tget_target_property(HEADERS_CXXOPTS cxxopts INTERFACE_INCLUDE_DIRECTORIES)\n\tget_target_property(HEADERS_SPDLOGS spdlog INTERFACE_INCLUDE_DIRECTORIES)\n\tget_target_property(HEADERS_FMT fmt INTERFACE_SYSTEM_INCLUDE_DIRECTORIES)\n\tget_target_property(HEADERS_RAPIDJSON rapidjson INTERFACE_SYSTEM_INCLUDE_DIRECTORIES)\n\tget_target_property(HEADERS_RANGE_V3 range-v3 INTERFACE_SYSTEM_INCLUDE_DIRECTORIES)\n\n\ttarget_include_directories(gmpm\n\t\tSYSTEM\n\t\tPRIVATE ${CMAKE_SOURCE_DIR}/Library\n\t\tPRIVATE ${HEADERS_CXXOPTS}\n\t\tPRIVATE ${HEADERS_SPDLOGS}\n\t\tPRIVATE ${HEADERS_FMT}\n\t\tPRIVATE ${HEADERS_RAPIDJSON}\n\t\tPRIVATE ${HEADERS_RANGE_V3}\n\t)\n\n\n\t#Copy scene files\n\n\tinstall(DIRECTORY\n\t\t${CMAKE_CURRENT_LIST_DIR}/scenes DESTINATION ${CMAKE_INSTALL_BINDIR}\n\t\t#FILES_MATCHING PATTERN \"*.json\"\n\t)\n\nendif()" }, { "path": "Projects/GMPM/constitutive_models.cuh", "content": "#ifndef CONSTITUTIVE_MODELS_CUH\n#define CONSTITUTIVE_MODELS_CUH\n#include \n#include \n\n#include \n\n#include \"settings.h\"\n\n//NOLINTNEXTLINE(cppcoreguidelines-macro-usage) Macro usage necessary here for preprocessor if\n#define USE_JOSH_FRACTURE_PAPER 1//Selects which solve is used\n\nnamespace mn {\n\n//Need this, cause we cannot partially instantiate function templates in current c++ version\ntemplate\nstruct ComputeStressIntermediate {\n\tT bm;\n\tT xi;\n\tT beta;\n\tT msqr;\n\tT log_jp;\n\tT cohesion;\n\tT yield_surface;\n\tbool hardening_on;\n\tbool volume_correction;\n};\n\n//NOLINTBEGIN(readability-magic-numbers, readability-identifier-naming) Magic numbers are formula specific; Common naming for this physical formulas\ntemplate\n__forceinline__ __device__ void compute_stress(const T volume, const T mu, const T lambda, std::array& F, std::array& PF, ComputeStressIntermediate& data);\n//NOLINTEND(readability-magic-numbers, readability-identifier-naming)\n\n//TODO: But maybe use names instead for better understanding\n//NOLINTBEGIN(readability-magic-numbers, readability-identifier-naming) Magic numbers are formula specific; Common naming for this physical formulas\ntemplate<>\n__forceinline__ __device__ void compute_stress(const float volume, const float mu, const float lambda, std::array& F, std::array& PF, ComputeStressIntermediate& data) {\n\t(void) data;\n\n\tstd::array U = {};\n\tstd::array S = {};\n\tstd::array V = {};\n\tmath::svd(F[0], F[3], F[6], F[1], F[4], F[7], F[2], F[5], F[8], U[0], U[3], U[6], U[1], U[4], U[7], U[2], U[5], U[8], S[0], S[1], S[2], V[0], V[3], V[6], V[1], V[4], V[7], V[2], V[5], V[8]);\n\tfloat J\t\t\t\t= S[0] * S[1] * S[2];\n\tfloat scaled_mu\t\t= 2.0f * mu;\n\tfloat scaled_lambda = lambda * (J - 1.0f);\n\tvec P_hat;\n\tP_hat[0] = scaled_mu * (S[0] - 1.f) + scaled_lambda * (S[1] * S[2]);\n\tP_hat[1] = scaled_mu * (S[1] - 1.f) + scaled_lambda * (S[0] * S[2]);\n\tP_hat[2] = scaled_mu * (S[2] - 1.f) + scaled_lambda * (S[0] * S[1]);\n\n\tvec P;\n\tP[0] = P_hat[0] * U[0] * V[0] + P_hat[1] * U[3] * V[3] + P_hat[2] * U[6] * V[6];\n\tP[1] = P_hat[0] * U[1] * V[0] + P_hat[1] * U[4] * V[3] + P_hat[2] * U[7] * V[6];\n\tP[2] = P_hat[0] * U[2] * V[0] + P_hat[1] * U[5] * V[3] + P_hat[2] * U[8] * V[6];\n\tP[3] = P_hat[0] * U[0] * V[1] + P_hat[1] * U[3] * V[4] + P_hat[2] * U[6] * V[7];\n\tP[4] = P_hat[0] * U[1] * V[1] + P_hat[1] * U[4] * V[4] + P_hat[2] * U[7] * V[7];\n\tP[5] = P_hat[0] * U[2] * V[1] + P_hat[1] * U[5] * V[4] + P_hat[2] * U[8] * V[7];\n\tP[6] = P_hat[0] * U[0] * V[2] + P_hat[1] * U[3] * V[5] + P_hat[2] * U[6] * V[8];\n\tP[7] = P_hat[0] * U[1] * V[2] + P_hat[1] * U[4] * V[5] + P_hat[2] * U[7] * V[8];\n\tP[8] = P_hat[0] * U[2] * V[2] + P_hat[1] * U[5] * V[5] + P_hat[2] * U[8] * V[8];\n\n\t/// PF'\n\tPF[0] = (P[0] * F[0] + P[3] * F[3] + P[6] * F[6]) * volume;\n\tPF[1] = (P[1] * F[0] + P[4] * F[3] + P[7] * F[6]) * volume;\n\tPF[2] = (P[2] * F[0] + P[5] * F[3] + P[8] * F[6]) * volume;\n\tPF[3] = (P[0] * F[1] + P[3] * F[4] + P[6] * F[7]) * volume;\n\tPF[4] = (P[1] * F[1] + P[4] * F[4] + P[7] * F[7]) * volume;\n\tPF[5] = (P[2] * F[1] + P[5] * F[4] + P[8] * F[7]) * volume;\n\tPF[6] = (P[0] * F[2] + P[3] * F[5] + P[6] * F[8]) * volume;\n\tPF[7] = (P[1] * F[2] + P[4] * F[5] + P[7] * F[8]) * volume;\n\tPF[8] = (P[2] * F[2] + P[5] * F[5] + P[8] * F[8]) * volume;\n}\n//NOLINTEND(readability-magic-numbers, readability-identifier-naming)\n\n//TODO: But maybe use names instead for better understanding\n//NOLINTBEGIN(readability-magic-numbers, readability-identifier-naming) Magic numbers are formula specific; Common naming for this physical formulas\ntemplate<>\n__forceinline__ __device__ void compute_stress(const float volume, const float mu, const float lambda, std::array& F, std::array& PF, ComputeStressIntermediate& data) {\n\t//FIXME: Explodes on impact. Not sure why. J gets very low. Clamping of all J prevents crash, but results are still wrong.\n\t(void) lambda;\n\n\tstd::array U = {};\n\tstd::array S = {};\n\tstd::array V = {};\n\tmath::svd(F[0], F[3], F[6], F[1], F[4], F[7], F[2], F[5], F[8], U[0], U[3], U[6], U[1], U[4], U[7], U[2], U[5], U[8], S[0], S[1], S[2], V[0], V[3], V[6], V[1], V[4], V[7], V[2], V[5], V[8]);\n\tfloat p0\t= data.bm * (static_cast(0.00001) + sinh(data.xi * (-data.log_jp > 0 ? -data.log_jp : 0)));\n\tfloat p_min = -data.beta * p0;\n\n\tfloat Je_trial = S[0] * S[1] * S[2];\n\n\t///< 0). calculate YS\n\tstd::array B_hat_trial = {S[0] * S[0], S[1] * S[1], S[2] * S[2]};\n\tfloat trace_B_hat_trial_divdim\t = (B_hat_trial[0] + B_hat_trial[1] + B_hat_trial[2]) / 3.f;\n\tfloat J_power_neg_2_d_mulmu\t\t = mu * powf(Je_trial, -2.f / 3.f);///< J^(-2/dim) * mu\n\tstd::array s_hat_trial = {J_power_neg_2_d_mulmu * (B_hat_trial[0] - trace_B_hat_trial_divdim), J_power_neg_2_d_mulmu * (B_hat_trial[1] - trace_B_hat_trial_divdim), J_power_neg_2_d_mulmu * (B_hat_trial[2] - trace_B_hat_trial_divdim)};\n\tfloat psi_kappa_partial_J\t\t = data.bm * 0.5f * (Je_trial - 1.f / Je_trial);\n\tfloat p_trial\t\t\t\t\t = -psi_kappa_partial_J * Je_trial;\n\n\tfloat y_s_half_coeff\t = 3.f / 2.f * (1 + 2.f * data.beta);///< a\n\tfloat y_p_half\t\t\t = (data.msqr * (p_trial - p_min) * (p_trial - p0));\n\tfloat s_hat_trial_sqrnorm = s_hat_trial[0] * s_hat_trial[0] + s_hat_trial[1] * s_hat_trial[1] + s_hat_trial[2] * s_hat_trial[2];\n\tfloat y\t\t\t\t\t = (y_s_half_coeff * s_hat_trial_sqrnorm) + y_p_half;\n\n\tif(\n\t\t//blockIdx.x == 0 && threadIdx.x == 0\n\t\tJe_trial < 0.1\n\t){\n\t\t//printf(\"%.32f %.32f %.32f, %.32f %.32f %.32f, %.32f %.32f %.32f # %.32f - \", F[0], F[1], F[2], F[3], F[4], F[5], F[6], F[7], F[8], Je_trial);\n\t}\n\n\t//< 1). update strain and hardening alpha(in log_jp)\n\n\t///< case 1, project to max tip of YS\n\tif(p_trial > p0) {\n\t\tfloat Je_new = sqrtf(-2.f * p0 / data.bm + 1.f);\n\t\tS[0] = S[1] = S[2]\t\t = powf(Je_new, 1.f / 3.f);\n\t\tstd::array New_F = {};\n\t\tmatmul_mat_diag_mat_t_3d(New_F, U, S, V);\n#pragma unroll 9\n\t\tfor(int i = 0; i < 9; i++) {\n\t\t\tF[i] = New_F[i];\n\t\t}\n\t\tif(data.hardening_on) {\n\t\t\tdata.log_jp += logf(Je_trial / Je_new);\n\t\t}\n\t}///< case 1 -- end\n\n\t/// case 2, project to min tip of YS\n\telse if(p_trial < p_min) {\n\t\tfloat Je_new = sqrtf(-2.f * p_min / data.bm + 1.f);\n\t\tS[0] = S[1] = S[2]\t\t = powf(Je_new, 1.f / 3.f);\n\t\tstd::array New_F = {};\n\t\tmatmul_mat_diag_mat_t_3d(New_F, U, S, V);\n#pragma unroll 9\n\t\tfor(int i = 0; i < 9; i++) {\n\t\t\tF[i] = New_F[i];\n\t\t}\n\t\tif(data.hardening_on) {\n\t\t\tdata.log_jp += logf(Je_trial / Je_new);\n\t\t}\n\t}///< case 2 -- end\n\n\t/// case 3, keep or project to YS by hardening\n\telse {\n\t\t///< outside YS\n\t\tif(y >= 1e-4) {\n\t\t\t////< yield surface projection\n\t\t\tfloat B_s_coeff = powf(Je_trial, 2.f / 3.f) / mu * sqrtf(-y_p_half / y_s_half_coeff) / sqrtf(s_hat_trial_sqrnorm);\n#pragma unroll 3\n\t\t\tfor(int i = 0; i < 3; i++) {\n\t\t\t\tS[i] = sqrtf(s_hat_trial[i] * B_s_coeff + trace_B_hat_trial_divdim);\n\t\t\t}\n\t\t\tstd::array New_F = {};\n\t\t\tmatmul_mat_diag_mat_t_3d(New_F, U, S, V);\n#pragma unroll 9\n\t\t\tfor(int i = 0; i < 9; i++) {\n\t\t\t\tF[i] = New_F[i];\n\t\t\t}\n\n\t\t\t////< hardening\n\t\t\tif(data.hardening_on && p0 > 1e-4 && p_trial < p0 - 1e-4 && p_trial > 1e-4 + p_min) {\n\t\t\t\tfloat p_center = (static_cast(1.0) - data.beta) * p0 / 2;\n#if USE_JOSH_FRACTURE_PAPER/// solve in 19 Josh Fracture paper\n\t\t\t\tfloat q_trial\t\t\t\t = sqrtf(3.f / 2.f * s_hat_trial_sqrnorm);\n\t\t\t\tstd::array direction = {p_center - p_trial, -q_trial};\n\t\t\t\tfloat direction_norm\t\t = sqrtf(direction[0] * direction[0] + direction[1] * direction[1]);\n\t\t\t\tdirection[0] /= direction_norm;\n\t\t\t\tdirection[1] /= direction_norm;\n\n\t\t\t\tfloat C = data.msqr * (p_center - p_min) * (p_center - p0);\n\t\t\t\tfloat B = data.msqr * direction[0] * (2 * p_center - p0 - p_min);\n\t\t\t\tfloat A = data.msqr * direction[0] * direction[0] + (1 + 2 * data.beta) * direction[1] * direction[1];\n\n\t\t\t\tfloat l1 = (-B + sqrtf(B * B - 4 * A * C)) / (2 * A);\n\t\t\t\tfloat l2 = (-B - sqrtf(B * B - 4 * A * C)) / (2 * A);\n\n\t\t\t\tfloat p1 = p_center + l1 * direction[0];\n\t\t\t\tfloat p2 = p_center + l2 * direction[0];\n#else/// solve in ziran - Compare_With_Physbam\n\t\t\t\tfloat aa = data.msqr * powf(p_trial - p_center, 2) / (y_s_half_coeff * s_hat_trial_sqrnorm);\n\t\t\t\tfloat dd = 1 + aa;\n\t\t\t\tfloat ff = aa * data.beta * p0 - aa * p0 - 2 * p_center;\n\t\t\t\tfloat gg = (p_center * p_center) - aa * data.beta * (p0 * p0);\n\t\t\t\tfloat zz = sqrtf(fabsf(ff * ff - 4 * dd * gg));\n\t\t\t\tfloat p1 = (-ff + zz) / (2 * dd);\n\t\t\t\tfloat p2 = (-ff - zz) / (2 * dd);\n#endif\n\n\t\t\t\tfloat p_fake\t = (p_trial - p_center) * (p1 - p_center) > 0 ? p1 : p2;\n\t\t\t\tfloat tmp_Je_sqr = (-2 * p_fake / data.bm + 1);\n\t\t\t\tfloat Je_new_fake = sqrtf(tmp_Je_sqr > 0 ? tmp_Je_sqr : -tmp_Je_sqr);\n\t\t\t\tif(Je_new_fake > 1e-4) {\n\t\t\t\t\tdata.log_jp += logf(Je_trial / Je_new_fake);\n\t\t\t\t}\n\t\t\t}\n\t\t}///< outside YS -- end\n\t}\t ///< case 3 --end\n\n\t//< 2). elasticity\n\t///< known: F(renewed), U, V, S(renewed)\n\t///< unknown: J, dev(FF^T)\n\tfloat J\t\t\t\t\t = S[0] * S[1] * S[2];\n\tstd::array b_dev = {};\n\tstd::array b\t = {};\n\tmatrix_matrix_tranpose_multiplication_3d(F, b);\n\tmatrix_deviatoric_3d(b, b_dev);\n\n\t//FIXME: Fail-safe test for precision error caused by compiler. Not placed in matrix_deviatoric_3d cause error does not seem to be detectable in there\n\tif(b[0] == 1.0f && b[1] == 1.0f && b[2] == 1.0f && (b_dev[0] != 0.0f || b_dev[4] != 0.0f || b_dev[8] != 0.0f)) {\n\t\t//NOLINTNEXTLINE(cppcoreguidelines-pro-type-vararg) Cuda has no other way to print; Numbers are array indices to be printed\n\t\tprintf(\"matrix_deviatoric_3d failed to get things write (probably compiler issue)\");\n\t}\n\n\t///< |f| = P * F^T * Volume\n\tfloat dev_b_coeff = mu * powf(J, -2.f / 3.f);\n\tfloat i_coeff\t = data.bm * .5f * ((J * J - 1.f) * 0.5f - logf(J));\n\tPF[0]\t\t\t = (dev_b_coeff * b_dev[0] + i_coeff) * volume;\n\tPF[1]\t\t\t = (dev_b_coeff * b_dev[1]) * volume;\n\tPF[2]\t\t\t = (dev_b_coeff * b_dev[2]) * volume;\n\tPF[3]\t\t\t = (dev_b_coeff * b_dev[3]) * volume;\n\tPF[4]\t\t\t = (dev_b_coeff * b_dev[4] + i_coeff) * volume;\n\tPF[5]\t\t\t = (dev_b_coeff * b_dev[5]) * volume;\n\tPF[6]\t\t\t = (dev_b_coeff * b_dev[6]) * volume;\n\tPF[7]\t\t\t = (dev_b_coeff * b_dev[7]) * volume;\n\tPF[8]\t\t\t = (dev_b_coeff * b_dev[8] + i_coeff) * volume;\n\n\tif(\n\t\t//blockIdx.x == 0 && threadIdx.x == 0\n\t\tisnan(PF[0])\n\t){\n\t\t//printf(\"%.32f %.32f %.32f, %.32f %.32f %.32f, %.32f %.32f %.32f # %.32f %.32f %.32f, %.32f %.32f %.32f, %.32f %.32f %.32f # %.32f %.32f - \", F[0], F[1], F[2], F[3], F[4], F[5], F[6], F[7], F[8], b_dev[0], b_dev[1], b_dev[2], b_dev[3], b_dev[4], b_dev[5], b_dev[6], b_dev[7], b_dev[8], i_coeff, J);\n\t}\n}\n//NOLINTEND(readability-magic-numbers, readability-identifier-naming)\n\n//TODO: But maybe use names instead for better understanding\n//NOLINTBEGIN(readability-magic-numbers, readability-identifier-naming) Magic numbers are formula specific; Common naming for this physical formulas\ntemplate<>\n__forceinline__ __device__ void compute_stress(const float volume, const float mu, const float lambda, std::array& F, std::array& PF, ComputeStressIntermediate& data) {\n\tstd::array U = {};\n\tstd::array S = {};\n\tstd::array V = {};\n\tmath::svd(F[0], F[3], F[6], F[1], F[4], F[7], F[2], F[5], F[8], U[0], U[3], U[6], U[1], U[4], U[7], U[2], U[5], U[8], S[0], S[1], S[2], V[0], V[3], V[6], V[1], V[4], V[7], V[2], V[5], V[8]);\n\tfloat scaled_mu = static_cast(2.0) * mu;\n\n\tstd::array epsilon = {};\n\tstd::array New_S\t = {};///< helper\n\tstd::array New_F\t = {};\n\n#pragma unroll 3\n\tfor(int i = 0; i < 3; i++) {\n\t\tfloat abs_S = S[i] > 0 ? S[i] : -S[i];\n\t\tabs_S\t\t= abs_S > static_cast(1e-4) ? abs_S : static_cast(1e-4);\n\t\tepsilon[i]\t= logf(abs_S) - data.cohesion;\n\t}\n\tfloat sum_epsilon\t= epsilon[0] + epsilon[1] + epsilon[2];\n\tfloat trace_epsilon = sum_epsilon + data.log_jp;\n\n\tstd::array epsilon_hat = {};\n#pragma unroll 3\n\tfor(int i = 0; i < 3; i++) {\n\t\tepsilon_hat[i] = epsilon[i] - (trace_epsilon / static_cast(3.0));\n\t}\n\n\tfloat epsilon_hat_norm = sqrtf(epsilon_hat[0] * epsilon_hat[0] + epsilon_hat[1] * epsilon_hat[1] + epsilon_hat[2] * epsilon_hat[2]);\n\n\t/* Calculate Plasticiy */\n\tif(trace_epsilon >= static_cast(0.0)) {///< case II: project to the cone tip\n\t\tNew_S[0] = New_S[1] = New_S[2] = expf(data.cohesion);\n\t\tmatmul_mat_diag_mat_t_3d(New_F, U, New_S, V);// new F_e\n\t\t\t\t\t\t\t\t\t\t\t\t\t /* Update F */\n#pragma unroll 9\n\t\tfor(int i = 0; i < 9; i++) {\n\t\t\tF[i] = New_F[i];\n\t\t}\n\t\tif(data.volume_correction) {\n\t\t\tdata.log_jp = data.beta * sum_epsilon + data.log_jp;\n\t\t}\n\t} else if(mu != 0) {\n\t\tdata.log_jp\t\t\t = 0;\n\t\tfloat delta_gamma\t = epsilon_hat_norm + (static_cast(3.0) * lambda + scaled_mu) / scaled_mu * trace_epsilon * data.yield_surface;\n\t\tstd::array H = {};\n\t\tif(delta_gamma <= 0) {///< case I: inside the yield surface cone\n#pragma unroll 3\n\t\t\tfor(int i = 0; i < 3; i++) {\n\t\t\t\tH[i] = epsilon[i] + data.cohesion;\n\t\t\t}\n\t\t} else {///< case III: project to the cone surface\n#pragma unroll 3\n\t\t\tfor(int i = 0; i < 3; i++) {\n\t\t\t\tH[i] = epsilon[i] - (delta_gamma / epsilon_hat_norm) * epsilon_hat[i] + data.cohesion;\n\t\t\t}\n\t\t}\n#pragma unroll 3\n\t\tfor(int i = 0; i < 3; i++) {\n\t\t\tNew_S[i] = expf(H[i]);\n\t\t}\n\t\tmatmul_mat_diag_mat_t_3d(New_F, U, New_S, V);// new F_e\n\t\t\t\t\t\t\t\t\t\t\t\t\t /* Update F */\n#pragma unroll 9\n\t\tfor(int i = 0; i < 9; i++) {\n\t\t\tF[i] = New_F[i];\n\t\t}\n\t} else {\n\t\t//TODO: What to do here? Just don't change values?\n\t}\n\n\t/* Elasticity -- Calculate Coefficient */\n\tstd::array New_S_log = {logf(New_S[0]), logf(New_S[1]), logf(New_S[2])};\n\tstd::array P_hat\t = {};\n\n\t// float S_inverse[3] = {1.f/S[0], 1.f/S[1], 1.f/S[2]}; // TO CHECK\n\t// float S_inverse[3] = {1.f / New_S[0], 1.f / New_S[1], 1.f / New_S[2]}; // TO\n\t// CHECK\n\tfloat trace_log_S = New_S_log[0] + New_S_log[1] + New_S_log[2];\n\n#pragma unroll 3\n\tfor(int i = 0; i < 3; i++) {\n\t\tP_hat[i] = (scaled_mu * New_S_log[i] + lambda * trace_log_S) / New_S[i];\n\t}\n\n\tstd::array P = {};\n\tmatmul_mat_diag_mat_t_3d(P, U, P_hat, V);\n\t///< |f| = P * F^T * Volume\n\tPF[0] = (P[0] * F[0] + P[3] * F[3] + P[6] * F[6]) * volume;\n\tPF[1] = (P[1] * F[0] + P[4] * F[3] + P[7] * F[6]) * volume;\n\tPF[2] = (P[2] * F[0] + P[5] * F[3] + P[8] * F[6]) * volume;\n\tPF[3] = (P[0] * F[1] + P[3] * F[4] + P[6] * F[7]) * volume;\n\tPF[4] = (P[1] * F[1] + P[4] * F[4] + P[7] * F[7]) * volume;\n\tPF[5] = (P[2] * F[1] + P[5] * F[4] + P[8] * F[7]) * volume;\n\tPF[6] = (P[0] * F[2] + P[3] * F[5] + P[6] * F[8]) * volume;\n\tPF[7] = (P[1] * F[2] + P[4] * F[5] + P[7] * F[8]) * volume;\n\tPF[8] = (P[2] * F[2] + P[5] * F[5] + P[8] * F[8]) * volume;\n}\n//NOLINTEND(readability-magic-numbers, readability-identifier-naming)\n\n}// namespace mn\n\n#endif" }, { "path": "Projects/GMPM/gmpm.cu", "content": "#include \n#include \n#include \n#include \n#include \n#include \n\n#include \n#include \n#include \n#include \n\n#include \"gmpm_simulator.cuh\"\nnamespace fs = std::filesystem;\n\n#include \n#include \n#include \nnamespace rj = rapidjson;\nnamespace {\nconst std::array K_TYPE_NAMES {\"Null\", \"False\", \"True\", \"Object\", \"Array\", \"String\", \"Number\"};\n}// namespace\n\n// dragon_particles.bin, 775196\n// cube256_2.bin, 1048576\n// two_dragons.bin, 388950\n\ndecltype(auto) load_model(std::size_t particle_counts, const std::string& filename) {\n\tstd::vector> rawpos(particle_counts);\n\tauto addr_str = std::string(AssetDirPath) + \"MpmParticles/\";\n\tFILE* f;\n\tfopen_s(&f, (addr_str + filename).c_str(), \"rb\");\n\tstd::fread(rawpos.data(), sizeof(float), rawpos.size() * mn::config::NUM_DIMENSIONS, f);\n\tstd::fclose(f);\n\treturn rawpos;\n}\n\nstruct SimulatorConfigs {\n\tint dim\t\t\t\t\t = 0;\n\tfloat dx\t\t\t\t = NAN;\n\tfloat dx_inv\t\t\t = NAN;\n\tint resolution\t\t\t = 0;\n\tfloat gravity\t\t\t = NAN;\n\tstd::vector offset = {};\n} const SIM_CONFIGS;\n\nnamespace {\ntemplate\ninline bool check_member(const T& model, const char* member) {\n\tif(!model.HasMember(member)) {\n\t\tfmt::print(\"Membert not found: {}\\n\", member);\n\t\treturn false;\n\t} else {\n\t\treturn true;\n\t}\n}\n}// namespace\n\n//NOLINTBEGIN(clang-analyzer-cplusplus.PlacementNew) check_member prevents the error case\nvoid parse_scene(const std::string& fn, std::unique_ptr& benchmark) {\n\tfs::path p {fn};\n\tif(!p.is_absolute()) {\n\t\tp = fs::relative(p);\n\t}\n\tif(!fs::exists(p)) {\n\t\tfmt::print(\"file not exist {}\\n\", fn);\n\t} else {\n\t\tstd::size_t size = fs::file_size(p);\n\t\tstd::string configs;\n\t\tconfigs.resize(size);\n\n\t\tstd::ifstream istrm(fn);\n\t\tif(!istrm.is_open()) {\n\t\t\tfmt::print(\"cannot open file {}\\n\", fn);\n\t\t} else {\n\t\t\tistrm.read(configs.data(), static_cast(configs.size()));\n\t\t}\n\t\tistrm.close();\n\t\tfmt::print(\"load the scene file of size {}\\n\", size);\n\n\t\trj::Document doc;\n\t\tdoc.Parse(configs.data());\n\t\tfor(rj::Value::ConstMemberIterator itr = doc.MemberBegin(); itr != doc.MemberEnd(); ++itr) {\n\t\t\tfmt::print(\"Scene member {} is {}\\n\", itr->name.GetString(), K_TYPE_NAMES[itr->value.GetType()]);\n\t\t}\n\t\t{\n\t\t\tauto it = doc.FindMember(\"simulation\");\n\t\t\tif(it != doc.MemberEnd()) {\n\t\t\t\tauto& sim = it->value;\n\t\t\t\tif(sim.IsObject()) {\n\t\t\t\t\tfmt::print(fg(fmt::color::cyan), \"simulation: gpuid[{}], defaultDt[{}], fps[{}], frames[{}]\\n\", sim[\"gpuid\"].GetInt(), sim[\"default_dt\"].GetFloat(), sim[\"fps\"].GetInt(), sim[\"frames\"].GetInt());\n\t\t\t\t\tbenchmark = std::make_unique(sim[\"gpuid\"].GetInt(), mn::Duration(sim[\"default_dt\"].GetFloat()), sim[\"fps\"].GetInt(), sim[\"frames\"].GetInt());\n\t\t\t\t}\n\t\t\t}\n\t\t}///< end simulation parsing\n\t\t{\n\t\t\tauto it = doc.FindMember(\"models\");\n\t\t\tif(it != doc.MemberEnd()) {\n\t\t\t\tif(it->value.IsArray()) {\n\t\t\t\t\tfmt::print(\"has {} models\\n\", it->value.Size());\n\t\t\t\t\tfor(auto& model: it->value.GetArray()) {\n\t\t\t\t\t\tif(!check_member(model, \"constitutive\") || !check_member(model, \"file\")) {\n\t\t\t\t\t\t\treturn;\n\t\t\t\t\t\t}\n\n\t\t\t\t\t\tstd::string constitutive {model[\"constitutive\"].GetString()};\n\n\t\t\t\t\t\tfmt::print(fg(fmt::color::green), \"model constitutive[{}], file[{}]\\n\", constitutive, model[\"file\"].GetString());\n\n\t\t\t\t\t\tfs::path p {model[\"file\"].GetString()};\n\n\t\t\t\t\t\tauto init_model = [&](auto& positions, auto& velocity) {\n\t\t\t\t\t\t\tif(constitutive == \"fixed_corotated\") {\n\t\t\t\t\t\t\t\tif(!check_member(model, \"rho\") || !check_member(model, \"volume\") || !check_member(model, \"youngs_modulus\") || !check_member(model, \"poisson_ratio\")) {\n\t\t\t\t\t\t\t\t\treturn;\n\t\t\t\t\t\t\t\t}\n\n\t\t\t\t\t\t\t\tbenchmark->init_model(positions, velocity);\n\t\t\t\t\t\t\t\tbenchmark->update_fr_parameters(model[\"rho\"].GetFloat(), model[\"volume\"].GetFloat(), model[\"youngs_modulus\"].GetFloat(), model[\"poisson_ratio\"].GetFloat());\n\t\t\t\t\t\t\t} else if(constitutive == \"jfluid\") {\n\t\t\t\t\t\t\t\tif(!check_member(model, \"rho\") || !check_member(model, \"volume\") || !check_member(model, \"bulk_modulus\") || !check_member(model, \"gamma\") || !check_member(model, \"viscosity\")) {\n\t\t\t\t\t\t\t\t\treturn;\n\t\t\t\t\t\t\t\t}\n\n\t\t\t\t\t\t\t\tbenchmark->init_model(positions, velocity);\n\t\t\t\t\t\t\t\tbenchmark->update_j_fluid_parameters(model[\"rho\"].GetFloat(), model[\"volume\"].GetFloat(), model[\"bulk_modulus\"].GetFloat(), model[\"gamma\"].GetFloat(), model[\"viscosity\"].GetFloat());\n\t\t\t\t\t\t\t} else if(constitutive == \"nacc\") {\n\t\t\t\t\t\t\t\tif(!check_member(model, \"rho\") || !check_member(model, \"volume\") || !check_member(model, \"youngs_modulus\") || !check_member(model, \"poisson_ratio\") || !check_member(model, \"beta\") || !check_member(model, \"xi\")) {\n\t\t\t\t\t\t\t\t\treturn;\n\t\t\t\t\t\t\t\t}\n\n\t\t\t\t\t\t\t\tbenchmark->init_model(positions, velocity);\n\t\t\t\t\t\t\t\tbenchmark->update_nacc_parameters(model[\"rho\"].GetFloat(), model[\"volume\"].GetFloat(), model[\"youngs_modulus\"].GetFloat(), model[\"poisson_ratio\"].GetFloat(), model[\"beta\"].GetFloat(), model[\"xi\"].GetFloat());\n\t\t\t\t\t\t\t} else if(constitutive == \"sand\") {\n\t\t\t\t\t\t\t\tbenchmark->init_model(positions, velocity);\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\tfmt::print(\"Unknown constitutive: {}\", constitutive);\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t};\n\t\t\t\t\t\tmn::vec offset;\n\t\t\t\t\t\tmn::vec span;\n\t\t\t\t\t\tmn::vec velocity;\n\t\t\t\t\t\tif(!check_member(model, \"offset\") || !check_member(model, \"span\") || !check_member(model, \"velocity\")) {\n\t\t\t\t\t\t\treturn;\n\t\t\t\t\t\t}\n\n\t\t\t\t\t\tfor(int d = 0; d < mn::config::NUM_DIMENSIONS; ++d) {\n\t\t\t\t\t\t\toffset[d]\t= model[\"offset\"].GetArray()[d].GetFloat();\n\t\t\t\t\t\t\tspan[d]\t\t= model[\"span\"].GetArray()[d].GetFloat();\n\t\t\t\t\t\t\tvelocity[d] = model[\"velocity\"].GetArray()[d].GetFloat();\n\t\t\t\t\t\t}\n\t\t\t\t\t\tif(p.extension() == \".sdf\") {\n\t\t\t\t\t\t\tauto positions = mn::read_sdf(model[\"file\"].GetString(), mn::config::MODEL_PPC, mn::config::G_DX, mn::config::G_DOMAIN_SIZE, offset, span);\n\t\t\t\t\t\t\tmn::IO::insert_job([&]() {\n\t\t\t\t\t\t\t\tmn::write_partio(p.stem().string() + \".bgeo\", positions);\n\t\t\t\t\t\t\t});\n\t\t\t\t\t\t\tmn::IO::flush();\n\t\t\t\t\t\t\tinit_model(positions, velocity);\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}///< end models parsing\n\t}\n}\n//NOLINTEND(clang-analyzer-cplusplus.PlacementNew)\n\nint main(int argc, char* argv[]) {\n\tmn::Cuda::startup();\n\n\tcxxopts::Options options(\"Scene_Loader\", \"Read simulation scene\");\n\toptions.add_options()(\"f,file\", \"Scene Configuration File\", cxxopts::value()->default_value(\"scenes/scene.json\"));\n\tauto results = options.parse(argc, argv);\n\tauto fn\t\t = results[\"file\"].as();\n\tfmt::print(\"loading scene [{}]\\n\", fn);\n\n\tstd::unique_ptr benchmark;\n\tparse_scene(fn, benchmark);\n\t/*\n\tbenchmark = std::make_unique(1, 1e-4, 24, 60);\n\n\tconstexpr auto LEN\t\t = 46;\n\tconstexpr auto STRIDE\t = 56;\n\tconstexpr auto MODEL_COUNT = 3;\n\tfor(int did = 0; did < 2; ++did) {\n\t\tstd::vector> model;\n\t\tfor(int i = 0; i < MODEL_COUNT; ++i) {\n\t\t\tauto idx = (did * MODEL_COUNT + i);\n\t\t\tmodel\t = sample_uniform_box(\n\t\t\t\t gdx,\n\t\t\t\t ivec3 {18 + (idx & 1 ? STRIDE : 0), 18, 18},\n\t\t\t\t ivec3 {18 + (idx & 1 ? STRIDE : 0) + LEN, 18 + LEN, 18 + LEN}\n\t\t\t );\n\t\t}\n\t\tbenchmark->init_model(\n\t\t\tmodel,\n\t\t\tvec {0.f, 0.f, 0.f}\n\t\t);\n\t}\n\t*/\n\tgetchar();\n\n\tbenchmark->main_loop();\n\t///\n\tmn::IO::flush();\n\tbenchmark.reset();\n\t///\n\tmn::Cuda::shutdown();\n\treturn 0;\n}" }, { "path": "Projects/GMPM/gmpm_simulator.cuh", "content": "#ifndef GMPM_SIMULATOR_CUH\n#define GMPM_SIMULATOR_CUH\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n\n#include \n#include \n#include \n#include \n#include \n\n#include \"grid_buffer.cuh\"\n#include \"hash_table.cuh\"\n#include \"mgmpm_kernels.cuh\"\n#include \"particle_buffer.cuh\"\n#include \"settings.h\"\n\nnamespace mn {\n\nstruct GmpmSimulator {\n\tstatic constexpr Duration DEFAULT_DT = Duration(1e-4);\n\tstatic constexpr int DEFAULT_FPS\t = 24;\n\tstatic constexpr int DEFAULT_FRAMES\t = 60;\n\n\tstatic constexpr int DEFAULT_CUDA_BLOCK_SIZE = 256;\n\n\tstatic constexpr size_t BIN_COUNT = 2;\n\n\tusing streamIdx\t\t = Cuda::StreamIndex;\n\tusing eventIdx\t\t = Cuda::EventIndex;\n\tusing host_allocator = HeapAllocator;\n\n\tstatic_assert(std::is_same_v, \"block index type is not int\");\n\n\tstruct DeviceAllocator {\t\t\t // hide the global one\n\t\tvoid* allocate(std::size_t bytes) {//NOLINT(readability-convert-member-functions-to-static) Method is designed to be a non-static class member\n\t\t\tvoid* ret = nullptr;\n\t\t\tcheck_cuda_errors(cudaMalloc(&ret, bytes));\n\t\t\treturn ret;\n\t\t}\n\n\t\tvoid deallocate(void* p, std::size_t size) {//NOLINT(readability-convert-member-functions-to-static) Method is designed to be a non-static class member\n\t\t\t(void) size;\n\t\t\tcheck_cuda_errors(cudaFree(p));\n\t\t}\n\t};\n\n\tstruct Intermediates {\n\t\tvoid* base;\n\n\t\tint* d_tmp;\n\t\tint* active_block_marks;\n\t\tint* destinations;\n\t\tint* sources;\n\t\tint* bin_sizes;\n\t\tfloat* d_max_vel;\n\t\t//NOLINTBEGIN(cppcoreguidelines-pro-bounds-pointer-arithmetic) Current c++ version does not yet support std::span\n\t\tvoid alloc(size_t max_block_count) {\n\t\t\t//NOLINTBEGIN(readability-magic-numbers) Magic numbers are variable count\n\t\t\tcheck_cuda_errors(cudaMalloc(&base, sizeof(int) * (max_block_count * 5 + 1)));\n\n\t\t\td_tmp\t\t\t = static_cast(base);\n\t\t\tactive_block_marks = static_cast(static_cast(static_cast(base) + sizeof(int) * max_block_count));\n\t\t\tdestinations\t = static_cast(static_cast(static_cast(base) + sizeof(int) * max_block_count * 2));\n\t\t\tsources\t\t\t = static_cast(static_cast(static_cast(base) + sizeof(int) * max_block_count * 3));\n\t\t\tbin_sizes\t\t = static_cast(static_cast(static_cast(base) + sizeof(int) * max_block_count * 4));\n\t\t\td_max_vel\t\t = static_cast(static_cast(static_cast(base) + sizeof(int) * max_block_count * 5));\n\t\t\t//NOLINTEND(readability-magic-numbers)\n\t\t}\n\t\t//NOLINTEND(cppcoreguidelines-pro-bounds-pointer-arithmetic)\n\t\tvoid dealloc() const {\n\t\t\tcudaDeviceSynchronize();\n\t\t\tcheck_cuda_errors(cudaFree(base));\n\t\t}\n\t\tvoid resize(size_t max_block_count) {\n\t\t\tdealloc();\n\t\t\talloc(max_block_count);\n\t\t}\n\t};\n\n\t///\n\tint gpuid;\n\tint nframes;\n\tint fps;\n\t/// animation runtime settings\n\tDuration dt;\n\tDuration next_dt;\n\tDuration dt_default;\n\tDuration cur_time;\n\tfloat max_vel;\n\tuint64_t cur_frame;\n\tuint64_t cur_step;\n\t/// data on device, double buffering\n\tstd::vector grid_blocks\t\t\t\t\t\t\t\t\t= {};\n\tstd::array, BIN_COUNT> particle_bins = {};\n\tstd::vector> partitions\t\t\t\t\t\t\t\t= {};///< with halo info\n\tstd::vector particles\t\t\t\t\t\t\t\t= {};\n\n\tIntermediates tmps;\n\n\t/// data on host\n\tchar rollid;\n\tstd::size_t cur_num_active_blocks;\n\tstd::vector cur_num_active_bins\t = {};\n\tstd::array checked_counts = {};\n\tstd::vector checked_bin_counts\t\t = {};\n\tfloat max_vels;\n\tint partition_block_count;\n\tint neighbor_block_count;\n\tint exterior_block_count;///< num blocks\n\tstd::vector bincount\t\t\t\t\t\t\t\t\t = {};\n\tstd::vector particle_counts\t\t\t\t\t\t = {};///< num particles\n\tstd::vector> model = {};\n\tstd::vector vel0\t\t\t\t\t\t\t\t\t\t = {};\n\n\texplicit GmpmSimulator(int gpu = 0, Duration dt = DEFAULT_DT, int fps = DEFAULT_FPS, int frames = DEFAULT_FRAMES)\n\t\t: gpuid(gpu)\n\t\t, dt_default(dt)\n\t\t, cur_time(Duration::zero())\n\t\t, rollid(0)\n\t\t, cur_frame(0)\n\t\t, cur_step(0)\n\t\t, fps(fps)\n\t\t, nframes(frames)\n\t\t, dt()\n\t\t, next_dt()\n\t\t, max_vel()\n\t\t, tmps()\n\t\t, cur_num_active_blocks()\n\t\t, max_vels()\n\t\t, partition_block_count()\n\t\t, neighbor_block_count()\n\t\t, exterior_block_count() {\n\t\t// data\n\t\tinitialize();\n\t}\n\t~GmpmSimulator() = default;\n\n\t//TODO: Maybe implement?\n\tGmpmSimulator(GmpmSimulator& other)\t\t\t\t= delete;\n\tGmpmSimulator(GmpmSimulator&& other)\t\t\t= delete;\n\tGmpmSimulator& operator=(GmpmSimulator& other)\t= delete;\n\tGmpmSimulator& operator=(GmpmSimulator&& other) = delete;\n\n\tvoid initialize() {\n\t\tauto& cu_dev = Cuda::ref_cuda_context(gpuid);\n\t\tcu_dev.set_context();\n\n\t\t//Allocate intermediate data for all blocks\n\t\ttmps.alloc(config::G_MAX_ACTIVE_BLOCK);\n\n\t\t//Create partitions and grid blocks\n\t\tfor(int copyid = 0; copyid < BIN_COUNT; copyid++) {\n\t\t\tgrid_blocks.emplace_back(DeviceAllocator {});\n\t\t\tpartitions.emplace_back(DeviceAllocator {}, config::G_MAX_ACTIVE_BLOCK);\n\t\t\tchecked_counts[copyid] = 0;\n\t\t}\n\n\t\tcu_dev.syncStream();\n\t\tcur_num_active_blocks = config::G_MAX_ACTIVE_BLOCK;\n\t}\n\n\ttemplate\n\tvoid init_model(const std::vector>& model, const mn::vec& v0) {\n\t\tauto& cu_dev = Cuda::ref_cuda_context(gpuid);\n\n\t\t//Create particle buffers and reserve buckets\n\t\tfor(int copyid = 0; copyid < BIN_COUNT; ++copyid) {\n\t\t\tparticle_bins[copyid].emplace_back(ParticleBuffer(DeviceAllocator {}, model.size() / config::G_BIN_CAPACITY + config::G_MAX_ACTIVE_BLOCK));\n\t\t\tmatch(particle_bins[copyid].back())([&](auto& particle_buffer) {\n\t\t\t\tparticle_buffer.reserve_buckets(DeviceAllocator {}, config::G_MAX_ACTIVE_BLOCK);\n\t\t\t});\n\t\t}\n\n\t\t//Set initial velocity\n\t\tvel0.emplace_back();\n\t\tfor(int i = 0; i < config::NUM_DIMENSIONS; ++i) {\n\t\t\tvel0.back()[i] = v0[i];\n\t\t}\n\n\t\t//Create array for initial particles\n\t\tparticles.emplace_back(spawn(DeviceAllocator {}, sizeof(float) * config::NUM_DIMENSIONS * model.size()));\n\n\t\t//Init bin counts\n\t\tcur_num_active_bins.emplace_back(config::G_MAX_PARTICLE_BIN);\n\t\tbincount.emplace_back(0);\n\t\tchecked_bin_counts.emplace_back(0);\n\n\t\t//Init particle counts\n\t\tparticle_counts.emplace_back(static_cast(model.size()));//NOTE: Explicic narrowing cast\n\n\t\tfmt::print(\"init {}-th model with {} particles\\n\", particle_bins[0].size() - 1, particle_counts.back());\n\n\t\t//Copy particle positions from host to device\n\t\tcudaMemcpyAsync(static_cast(&particles.back().val_1d(_0, 0)), model.data(), sizeof(std::array) * model.size(), cudaMemcpyDefault, cu_dev.stream_compute());\n\t\tcu_dev.syncStream();\n\n\t\t//Write out initial state to file\n\t\tstd::string fn = std::string {\"model\"} + \"_id[\" + std::to_string(particle_bins[0].size() - 1) + \"]_frame[0].bgeo\";\n\t\tIO::insert_job([fn, model]() {\n\t\t\twrite_partio(fn, model);\n\t\t});\n\t\tIO::flush();\n\t}\n\n\tvoid update_fr_parameters(float rho, float vol, float ym, float pr) {\n\t\tmatch(particle_bins[0].back())(\n\t\t\t[&](auto& particle_buffer) {},\n\t\t\t[&](ParticleBuffer& particle_buffer) {\n\t\t\t\tparticle_buffer.update_parameters(rho, vol, ym, pr);\n\t\t\t}\n\t\t);\n\t\tmatch(particle_bins[1].back())(\n\t\t\t[&](auto& particle_buffer) {},\n\t\t\t[&](ParticleBuffer& particle_buffer) {\n\t\t\t\tparticle_buffer.update_parameters(rho, vol, ym, pr);\n\t\t\t}\n\t\t);\n\t}\n\n\tvoid update_j_fluid_parameters(float rho, float vol, float bulk, float gamma, float viscosity) {\n\t\tmatch(particle_bins[0].back())(\n\t\t\t[&](auto& particle_buffer) {},\n\t\t\t[&](ParticleBuffer& particle_buffer) {\n\t\t\t\tparticle_buffer.update_parameters(rho, vol, bulk, gamma, viscosity);\n\t\t\t}\n\t\t);\n\t\tmatch(particle_bins[1].back())(\n\t\t\t[&](auto& particle_buffer) {},\n\t\t\t[&](ParticleBuffer& particle_buffer) {\n\t\t\t\tparticle_buffer.update_parameters(rho, vol, bulk, gamma, viscosity);\n\t\t\t}\n\t\t);\n\t}\n\n\tvoid update_nacc_parameters(float rho, float vol, float ym, float pr, float beta, float xi) {\n\t\tmatch(particle_bins[0].back())(\n\t\t\t[&](auto& particle_buffer) {},\n\t\t\t[&](ParticleBuffer& particle_buffer) {\n\t\t\t\tparticle_buffer.update_parameters(rho, vol, ym, pr, beta, xi);\n\t\t\t}\n\t\t);\n\t\tmatch(particle_bins[1].back())(\n\t\t\t[&](auto& particle_buffer) {},\n\t\t\t[&](ParticleBuffer& particle_buffer) {\n\t\t\t\tparticle_buffer.update_parameters(rho, vol, ym, pr, beta, xi);\n\t\t\t}\n\t\t);\n\t}\n\n\t//Sum up count values from in and store them in out\n\ttemplate\n\tvoid exclusive_scan(int count, int const* const in, int* out, CudaContext& cu_dev) {\n\t\tauto policy = thrust::cuda::par.on(static_cast(cu_dev.stream_compute()));\n\t\tthrust::exclusive_scan(policy, get_device_ptr(in), get_device_ptr(in) + count, get_device_ptr(out));\n\t\t/*\n\t\tstd::size_t temp_storage_bytes = 0;\n\t\tauto plus_op\t\t\t\t = [] __device__(const int& a, const int& b) {\n\t\t\t return a + b;\n\t\t};\n\t\tcheck_cuda_errors(cub::DeviceScan::ExclusiveScan(nullptr, temp_storage_bytes, in, out, plus_op, 0, count, cu_dev.stream_compute()));\n\t\tvoid* d_tmp = tmps[cu_dev.get_dev_id()].d_tmp;\n\t\tcheck_cuda_errors(cub::DeviceScan::ExclusiveScan(d_tmp, temp_storage_bytes, in, out, plus_op, 0, count, cu_dev.stream_compute()));\n\t\t*/\n\t}\n\n\tfloat get_mass(int id = 0) {\n\t\treturn match(particle_bins[rollid][id])([&](const auto& particle_buffer) {\n\t\t\treturn particle_buffer.mass;\n\t\t});\n\t}\n\n\t[[nodiscard]] int get_model_count() const noexcept {\n\t\treturn static_cast(particle_bins[0].size());//NOTE: Explicit narrowing cast (But we should not have that much models anyway.)\n\t}\n\n\t//Increase bin and active block count if too low\n\tvoid check_capacity() {\n\t\t//TODO: Is that right? Maybe create extra parameter for this?\n\t\t//NOLINTBEGIN(readability-magic-numbers) Magic numbers are resize thresholds?\n\t\tif(exterior_block_count > cur_num_active_blocks * config::NUM_DIMENSIONS / 4 && checked_counts[0] == 0) {\n\t\t\tcur_num_active_blocks = cur_num_active_blocks * config::NUM_DIMENSIONS / 2;\n\t\t\tchecked_counts[0]\t = 2;\n\t\t\tfmt::print(fmt::emphasis::bold, \"resizing blocks {} -> {}\\n\", exterior_block_count, cur_num_active_blocks);\n\t\t}\n\n\t\tfor(int i = 0; i < get_model_count(); ++i) {\n\t\t\tif(bincount[i] > cur_num_active_bins[i] * config::NUM_DIMENSIONS / 4 && checked_bin_counts[i] == 0) {\n\t\t\t\tcur_num_active_bins[i] = cur_num_active_bins[i] * config::NUM_DIMENSIONS / 2;\n\t\t\t\tchecked_bin_counts[i] = 2;\n\t\t\t\tfmt::print(fmt::emphasis::bold, \"resizing bins {} -> {}\\n\", bincount[i], cur_num_active_bins[i]);\n\t\t\t}\n\t\t}\n\t\t//NOLINTEND(readability-magic-numbers)\n\t}\n\n\t//NOLINTBEGIN(cppcoreguidelines-pro-bounds-pointer-arithmetic) Current c++ version does not yet support std::span\n\tvoid main_loop() {\n\t\t/// initial\n\t\tconst Duration seconds_per_frame(Duration(1) / Duration(fps));\n\t\t{\n\t\t\tfloat max_vel = 0.f;\n\t\t\tfor(int i = 0; i < get_model_count(); ++i) {\n\t\t\t\tconst float vel_norm = std::sqrt(vel0[i].l2NormSqr());\n\t\t\t\tif(vel_norm > max_vel) {\n\t\t\t\t\tmax_vel = vel_norm;\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tdt = compute_dt(max_vel, Duration::zero(), seconds_per_frame, dt_default);\n\t\t}\n\n\t\tfmt::print(fmt::emphasis::bold, \"{} --{}--> {}, defaultDt: {}\\n\", cur_time.count(), dt.count(), seconds_per_frame.count(), dt_default.count());\n\t\tinitial_setup();\n\n\t\tcur_time = Duration::zero();\n\t\tfor(cur_frame = 1; cur_frame <= nframes; ++cur_frame) {\n\t\t\tconst Duration next_time = cur_time + seconds_per_frame;\n\t\t\tfor(Duration current_step_time = Duration::zero(); current_step_time < seconds_per_frame; current_step_time += dt, cur_time += dt, cur_step++) {\n\t\t\t\t//Calculate maximum grid velocity and update the grid velocity\n\t\t\t\t{\n\t\t\t\t\tauto& cu_dev = Cuda::ref_cuda_context(gpuid);\n\n\t\t\t\t\t/// check capacity\n\t\t\t\t\tcheck_capacity();\n\n\t\t\t\t\tCudaTimer timer {cu_dev.stream_compute()};\n\t\t\t\t\ttimer.tick();\n\n\t\t\t\t\tfloat* d_max_vel = tmps.d_max_vel;\n\t\t\t\t\t//Initialize max_vel with 0\n\t\t\t\t\tcheck_cuda_errors(cudaMemsetAsync(d_max_vel, 0, sizeof(float), cu_dev.stream_compute()));\n\n\t\t\t\t\t//Update the grid velocity\n\t\t\t\t\t//floor(neighbor_block_count/G_NUM_GRID_BLOCKS_PER_CUDA_BLOCK); G_NUM_WARPS_PER_CUDA_BLOCK (>= G_NUM_GRID_BLOCKS_PER_CUDA_BLOCK)\n\t\t\t\t\tcu_dev.compute_launch({(neighbor_block_count + config::G_NUM_GRID_BLOCKS_PER_CUDA_BLOCK - 1) / config::G_NUM_GRID_BLOCKS_PER_CUDA_BLOCK, config::G_NUM_WARPS_PER_CUDA_BLOCK * config::CUDA_WARP_SIZE * config::G_NUM_WARPS_PER_GRID_BLOCK}, update_grid_velocity_query_max, static_cast(neighbor_block_count), grid_blocks[0], partitions[rollid], dt, d_max_vel);\n\n\t\t\t\t\t//Copy maximum velocity to host site\n\t\t\t\t\tcheck_cuda_errors(cudaMemcpyAsync(&max_vels, d_max_vel, sizeof(float), cudaMemcpyDefault, cu_dev.stream_compute()));\n\n\t\t\t\t\ttimer.tock(fmt::format(\"GPU[{}] frame {} step {} grid_update_query\", gpuid, cur_frame, cur_step));\n\t\t\t\t}\n\n\t\t\t\t/// host: compute maxvel & next dt\n\t\t\t\tfloat max_vel = max_vels;\n\t\t\t\t// if (max_vels > max_vel)\n\t\t\t\t// max_vel = max_vels[id];\n\n\t\t\t\t//If our maximum velocity is infinity our computation will crash, so we stop here.\n\t\t\t\tif(std::isinf(max_vel)) {\n\t\t\t\t\tstd::cout << \"Maximum velocity is infinity\" << std::endl;\n\t\t\t\t\tgoto outer_loop_end;\n\t\t\t\t}\n\n\t\t\t\tmax_vel = std::sqrt(max_vel);// this is a bug, should insert this line\n\t\t\t\tnext_dt = compute_dt(max_vel, current_step_time, seconds_per_frame, dt_default);\n\t\t\t\tfmt::print(fmt::emphasis::bold, \"{} --{}--> {}, defaultDt: {}, max_vel: {}\\n\", cur_time.count(), next_dt.count(), next_time.count(), dt_default.count(), max_vel);\n\n\t\t\t\t/// g2p2g\n\t\t\t\t{\n\t\t\t\t\tauto& cu_dev = Cuda::ref_cuda_context(gpuid);\n\t\t\t\t\tCudaTimer timer {cu_dev.stream_compute()};\n\n\t\t\t\t\t//Resize particle buffers if we increased the size of active bins\n\t\t\t\t\t//This also removes all particle data of next particle buffer but does not clear it\n\t\t\t\t\tfor(int i = 0; i < get_model_count(); ++i) {\n\t\t\t\t\t\tif(checked_bin_counts[i] > 0) {\n\t\t\t\t\t\t\tmatch(particle_bins[(rollid + 1) % BIN_COUNT][i])([this, &i](auto& particle_buffer) {\n\t\t\t\t\t\t\t\tparticle_buffer.resize(DeviceAllocator {}, cur_num_active_bins[i]);\n\t\t\t\t\t\t\t});\n\t\t\t\t\t\t\tchecked_bin_counts[i]--;\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\n\t\t\t\t\ttimer.tick();\n\n\t\t\t\t\t//Clear the grid\n\t\t\t\t\tgrid_blocks[1].reset(neighbor_block_count, cu_dev);\n\n\t\t\t\t\t//Perform G2P2G step\n\t\t\t\t\tfor(int i = 0; i < get_model_count(); ++i) {\n\t\t\t\t\t\t//First clear the count of particles per cell for next buffer\n\t\t\t\t\t\tmatch(particle_bins[(rollid + 1) % BIN_COUNT][i])([this, &cu_dev](auto& particle_buffer) {\n\t\t\t\t\t\t\tcheck_cuda_errors(cudaMemsetAsync(particle_buffer.cell_particle_counts, 0, sizeof(int) * exterior_block_count * config::G_BLOCKVOLUME, cu_dev.stream_compute()));\n\t\t\t\t\t\t});\n\n\t\t\t\t\t\t//Perform g2p2g\n\t\t\t\t\t\tmatch(particle_bins[rollid][i])([this, &cu_dev, &i](const auto& particle_buffer) {\n\t\t\t\t\t\t\t//partition_block_count; G_PARTICLE_BATCH_CAPACITY\n\t\t\t\t\t\t\tcu_dev.compute_launch({partition_block_count, config::G_PARTICLE_BATCH_CAPACITY}, g2p2g, dt, next_dt, particle_buffer, get>(particle_bins[(rollid + 1) % BIN_COUNT][i]), partitions[(rollid + 1) % BIN_COUNT], partitions[rollid], grid_blocks[0], grid_blocks[1]);\n\t\t\t\t\t\t});\n\t\t\t\t\t}\n\t\t\t\t\tcu_dev.syncStream();\n\n\t\t\t\t\ttimer.tock(fmt::format(\"GPU[{}] frame {} step {} g2p2g\", gpuid, cur_frame, cur_step));\n\n\t\t\t\t\t//Resize partition if we increased the size of active blocks\n\t\t\t\t\t//This also deletes current particle buffer meta data.\n\t\t\t\t\tif(checked_counts[0] > 0) {\n\t\t\t\t\t\tpartitions[(rollid + 1) % BIN_COUNT].resize_partition(DeviceAllocator {}, cur_num_active_blocks);\n\t\t\t\t\t\tfor(int i = 0; i < get_model_count(); ++i) {\n\t\t\t\t\t\t\tmatch(particle_bins[rollid][i])([this, &cu_dev](auto& particle_buffer) {\n\t\t\t\t\t\t\t\tparticle_buffer.reserve_buckets(DeviceAllocator {}, cur_num_active_blocks);\n\t\t\t\t\t\t\t});\n\t\t\t\t\t\t}\n\t\t\t\t\t\tchecked_counts[0]--;\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\t/// update partition\n\t\t\t\t{\n\t\t\t\t\tauto& cu_dev = Cuda::ref_cuda_context(gpuid);\n\t\t\t\t\tCudaTimer timer {cu_dev.stream_compute()};\n\n\t\t\t\t\ttimer.tick();\n\n\t\t\t\t\t//Copy cell buckets from partition to next particle buffer\n\t\t\t\t\tfor(int i = 0; i < get_model_count(); ++i) {\n\t\t\t\t\t\tmatch(particle_bins[(rollid + 1) % BIN_COUNT][i])([this, &cu_dev](auto& particle_buffer) {\n\t\t\t\t\t\t\t//First init sizes with 0\n\t\t\t\t\t\t\tcheck_cuda_errors(cudaMemsetAsync(particle_buffer.particle_bucket_sizes, 0, sizeof(int) * (exterior_block_count + 1), cu_dev.stream_compute()));\n\n\t\t\t\t\t\t\t//exterior_block_count; G_BLOCKVOLUME\n\t\t\t\t\t\t\tcu_dev.compute_launch({exterior_block_count, config::G_BLOCKVOLUME}, cell_bucket_to_block, particle_buffer.cell_particle_counts, particle_buffer.cellbuckets, particle_buffer.particle_bucket_sizes, particle_buffer.blockbuckets);\n\t\t\t\t\t\t\t// partitions[rollid].buildParticleBuckets(cu_dev, exterior_block_count);\n\t\t\t\t\t\t});\n\t\t\t\t\t}\n\n\t\t\t\t\tint* active_block_marks = tmps.active_block_marks;\n\t\t\t\t\tint* destinations\t\t= tmps.destinations;\n\t\t\t\t\tint* sources\t\t\t= tmps.sources;\n\t\t\t\t\t//Clear marks\n\t\t\t\t\tcheck_cuda_errors(cudaMemsetAsync(active_block_marks, 0, sizeof(int) * neighbor_block_count, cu_dev.stream_compute()));\n\n\t\t\t\t\t//Mark cells that have mass bigger 0.0\n\t\t\t\t\t//floor(neighbor_block_count * config::G_BLOCKVOLUME/G_PARTICLE_BATCH_CAPACITY); G_PARTICLE_BATCH_CAPACITY\n\t\t\t\t\tcu_dev.compute_launch({(neighbor_block_count * config::G_BLOCKVOLUME + config::G_PARTICLE_BATCH_CAPACITY - 1) / config::G_PARTICLE_BATCH_CAPACITY, config::G_PARTICLE_BATCH_CAPACITY}, mark_active_grid_blocks, static_cast(neighbor_block_count), grid_blocks[1], active_block_marks);\n\n\t\t\t\t\t//Clear marks\n\t\t\t\t\tcheck_cuda_errors(cudaMemsetAsync(sources, 0, sizeof(int) * (exterior_block_count + 1), cu_dev.stream_compute()));\n\n\t\t\t\t\t//Mark particle buckets that have at least one particle\n\t\t\t\t\tfor(int i = 0; i < get_model_count(); ++i) {\n\t\t\t\t\t\tmatch(particle_bins[(rollid + 1) % BIN_COUNT][i])([this, &cu_dev, &sources](auto& particle_buffer) {\n\t\t\t\t\t\t\t//floor((exterior_block_count + 1)/G_PARTICLE_BATCH_CAPACITY); G_PARTICLE_BATCH_CAPACITY\n\t\t\t\t\t\t\tcu_dev.compute_launch({exterior_block_count / config::G_PARTICLE_BATCH_CAPACITY + 1, config::G_PARTICLE_BATCH_CAPACITY}, mark_active_particle_blocks, exterior_block_count + 1, particle_buffer.particle_bucket_sizes, sources);\n\t\t\t\t\t\t});\n\t\t\t\t\t}\n\n\t\t\t\t\t//Sum up number of active buckets and calculate offsets (empty buckets are collapsed\n\t\t\t\t\texclusive_scan(exterior_block_count + 1, sources, destinations, cu_dev);\n\n\t\t\t\t\t/// building new partition\n\n\t\t\t\t\t//Store new bucket count\n\t\t\t\t\tcheck_cuda_errors(cudaMemcpyAsync(partitions[(rollid + 1) % BIN_COUNT].count, destinations + exterior_block_count, sizeof(int), cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\t\t\t\tcheck_cuda_errors(cudaMemcpyAsync(&partition_block_count, destinations + exterior_block_count, sizeof(int), cudaMemcpyDefault, cu_dev.stream_compute()));\n\n\t\t\t\t\t//Calculate indices of block by position\n\t\t\t\t\t//floor(exterior_block_count/DEFAULT_CUDA_BLOCK_SIZE); DEFAULT_CUDA_BLOCK_SIZE\n\t\t\t\t\tcu_dev.compute_launch({(exterior_block_count + DEFAULT_CUDA_BLOCK_SIZE - 1) / DEFAULT_CUDA_BLOCK_SIZE, DEFAULT_CUDA_BLOCK_SIZE}, exclusive_scan_inverse, exterior_block_count, static_cast(destinations), sources);\n\n\t\t\t\t\t//Reset partitions\n\t\t\t\t\tpartitions[(rollid + 1) % BIN_COUNT].reset_table(cu_dev.stream_compute());\n\t\t\t\t\tcu_dev.syncStream();\n\n\t\t\t\t\t//Check size\n\t\t\t\t\tif(partition_block_count > config::G_MAX_ACTIVE_BLOCK) {\n\t\t\t\t\t\tstd::cerr << \"Too much active blocks: \" << partition_block_count << std::endl;\n\t\t\t\t\t\tstd::abort();\n\t\t\t\t\t}\n\n\t\t\t\t\t//Reinsert buckets\n\t\t\t\t\t//floor(partition_block_count/G_PARTICLE_BATCH_CAPACITY); G_PARTICLE_BATCH_CAPACITY\n\t\t\t\t\tcu_dev.compute_launch({(partition_block_count + config::G_PARTICLE_BATCH_CAPACITY - 1) / config::G_PARTICLE_BATCH_CAPACITY, config::G_PARTICLE_BATCH_CAPACITY}, update_partition, static_cast(partition_block_count), static_cast(sources), partitions[rollid], partitions[(rollid + 1) % BIN_COUNT]);\n\n\t\t\t\t\t//Copy block buckets and sizes from next particle buffer to current particle buffer\n\t\t\t\t\tfor(int i = 0; i < get_model_count(); ++i) {\n\t\t\t\t\t\tmatch(particle_bins[(rollid + 1) % BIN_COUNT][i])([this, &cu_dev, &sources, &i](auto& particle_buffer) {\n\t\t\t\t\t\t\tauto& next_particle_buffer = get>(particle_bins[rollid][i]);\n\t\t\t\t\t\t\t//partition_block_count; G_PARTICLE_BATCH_CAPACITY\n\t\t\t\t\t\t\tcu_dev.compute_launch({partition_block_count, config::G_PARTICLE_BATCH_CAPACITY}, update_buckets, static_cast(partition_block_count), static_cast(sources), particle_buffer, next_particle_buffer);\n\t\t\t\t\t\t});\n\t\t\t\t\t}\n\n\t\t\t\t\t//Compute bin capacities, bin offsets and the summed bin size for current particle buffer\n\t\t\t\t\tint* bin_sizes = tmps.bin_sizes;\n\t\t\t\t\tfor(int i = 0; i < get_model_count(); ++i) {\n\t\t\t\t\t\tmatch(particle_bins[rollid][i])([this, &cu_dev, &bin_sizes, &i](auto& particle_buffer) {\n\t\t\t\t\t\t\t//floor((exterior_block_count + 1)/G_PARTICLE_BATCH_CAPACITY); G_PARTICLE_BATCH_CAPACITY\n\t\t\t\t\t\t\tcu_dev.compute_launch({partition_block_count / config::G_PARTICLE_BATCH_CAPACITY + 1, config::G_PARTICLE_BATCH_CAPACITY}, compute_bin_capacity, partition_block_count + 1, static_cast(particle_buffer.particle_bucket_sizes), bin_sizes);\n\n\t\t\t\t\t\t\t//Stores aggregated bin sizes in particle_buffer\n\t\t\t\t\t\t\texclusive_scan(partition_block_count + 1, bin_sizes, particle_buffer.bin_offsets, cu_dev);\n\n\t\t\t\t\t\t\t//Stores last aggregated size == whole size in bincount\n\t\t\t\t\t\t\tcheck_cuda_errors(cudaMemcpyAsync(&bincount[i], particle_buffer.bin_offsets + partition_block_count, sizeof(int), cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\t\t\t\t\t\tcu_dev.syncStream();\n\t\t\t\t\t\t});\n\t\t\t\t\t}\n\n\t\t\t\t\ttimer.tock(fmt::format(\"GPU[{}] frame {} step {} update_partition\", gpuid, cur_frame, cur_step));\n\n\t\t\t\t\ttimer.tick();\n\n\t\t\t\t\t//Activate blocks near active blocks\n\t\t\t\t\t//floor(partition_block_count/G_PARTICLE_BATCH_CAPACITY); G_PARTICLE_BATCH_CAPACITY\n\t\t\t\t\tcu_dev.compute_launch({(partition_block_count + config::G_PARTICLE_BATCH_CAPACITY - 1) / config::G_PARTICLE_BATCH_CAPACITY, config::G_PARTICLE_BATCH_CAPACITY}, register_neighbor_blocks, static_cast(partition_block_count), partitions[(rollid + 1) % BIN_COUNT]);\n\n\t\t\t\t\t//Retrieve total count\n\t\t\t\t\tauto prev_neighbor_block_count = neighbor_block_count;\n\t\t\t\t\tcheck_cuda_errors(cudaMemcpyAsync(&neighbor_block_count, partitions[(rollid + 1) % BIN_COUNT].count, sizeof(int), cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\t\t\t\tcu_dev.syncStream();\n\n\t\t\t\t\t//Check size\n\t\t\t\t\tif(neighbor_block_count > config::G_MAX_ACTIVE_BLOCK) {\n\t\t\t\t\t\tstd::cerr << \"Too much neighbour blocks: \" << partition_block_count << std::endl;\n\t\t\t\t\t\tstd::abort();\n\t\t\t\t\t}\n\n\t\t\t\t\ttimer.tock(fmt::format(\"GPU[{}] frame {} step {} build_partition_for_grid\", gpuid, cur_frame, cur_step));\n\n\t\t\t\t\t//Resize grid if necessary\n\t\t\t\t\tif(checked_counts[0] > 0) {\n\t\t\t\t\t\tgrid_blocks[0].resize(DeviceAllocator {}, cur_num_active_blocks);\n\t\t\t\t\t}\n\n\t\t\t\t\ttimer.tick();\n\n\t\t\t\t\t//Clear the grid\n\t\t\t\t\tgrid_blocks[0].reset(exterior_block_count, cu_dev);\n\n\t\t\t\t\t//Copy values from old grid for active blocks\n\t\t\t\t\t//prev_neighbor_block_count; G_BLOCKVOLUME\n\t\t\t\t\tcu_dev.compute_launch({prev_neighbor_block_count, config::G_BLOCKVOLUME}, copy_selected_grid_blocks, static_cast(partitions[rollid].active_keys), partitions[(rollid + 1) % BIN_COUNT], static_cast(active_block_marks), grid_blocks[1], grid_blocks[0]);\n\t\t\t\t\tcu_dev.syncStream();\n\n\t\t\t\t\ttimer.tock(fmt::format(\"GPU[{}] frame {} step {} copy_grid_blocks\", gpuid, cur_frame, cur_step));\n\n\t\t\t\t\t//Resize grid if necessary\n\t\t\t\t\tif(checked_counts[0] > 0) {\n\t\t\t\t\t\tgrid_blocks[1].resize(DeviceAllocator {}, cur_num_active_blocks);\n\t\t\t\t\t\ttmps.resize(cur_num_active_blocks);\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\t{\n\t\t\t\t\tauto& cu_dev = Cuda::ref_cuda_context(gpuid);\n\t\t\t\t\tCudaTimer timer {cu_dev.stream_compute()};\n\n\t\t\t\t\ttimer.tick();\n\n\t\t\t\t\t//Activate blocks near active blocks, including those before that block\n\t\t\t\t\t//floor(partition_block_count/G_PARTICLE_BATCH_CAPACITY); G_PARTICLE_BATCH_CAPACITY\n\t\t\t\t\tcu_dev.compute_launch({(partition_block_count + config::G_PARTICLE_BATCH_CAPACITY - 1) / config::G_PARTICLE_BATCH_CAPACITY, config::G_PARTICLE_BATCH_CAPACITY}, register_exterior_blocks, static_cast(partition_block_count), partitions[(rollid + 1) % BIN_COUNT]);\n\n\t\t\t\t\t//Retrieve total count\n\t\t\t\t\tcheck_cuda_errors(cudaMemcpyAsync(&exterior_block_count, partitions[(rollid + 1) % BIN_COUNT].count, sizeof(int), cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\t\t\t\tcu_dev.syncStream();\n\n\t\t\t\t\t//Check size\n\t\t\t\t\tif(exterior_block_count > config::G_MAX_ACTIVE_BLOCK) {\n\t\t\t\t\t\tstd::cerr << \"Too much exterior blocks: \" << partition_block_count << std::endl;\n\t\t\t\t\t\tstd::abort();\n\t\t\t\t\t}\n\n\t\t\t\t\tfmt::print(fmt::emphasis::bold | fg(fmt::color::yellow), \"block count on device {}: {}, {}, {} [{}]\\n\", gpuid, partition_block_count, neighbor_block_count, exterior_block_count, cur_num_active_blocks);\n\t\t\t\t\tfor(int i = 0; i < get_model_count(); ++i) {\n\t\t\t\t\t\tfmt::print(fmt::emphasis::bold | fg(fmt::color::yellow), \"bin count on device {}: model {}: {} [{}]\\n\", gpuid, i, bincount[i], cur_num_active_bins[i]);\n\t\t\t\t\t}\n\t\t\t\t\ttimer.tock(fmt::format(\"GPU[{}] frame {} step {} build_partition_for_particles\", gpuid, cur_frame, cur_step));\n\t\t\t\t}\n\t\t\t\trollid = static_cast((rollid + 1) % BIN_COUNT);\n\t\t\t\tdt\t = next_dt;\n\t\t\t}\n\t\t\tIO::flush();\n\t\t\toutput_model();\n\t\t\tfmt::print(\n\t\t\t\tfmt::emphasis::bold | fg(fmt::color::red),\n\t\t\t\t\"-----------------------------------------------------------\"\n\t\t\t\t\"-----\\n\"\n\t\t\t);\n\t\t}\n\touter_loop_end:\n\t\t(void) nullptr;//We need a statement to have a valid jump label\n\t}\n\t//NOLINTEND(cppcoreguidelines-pro-bounds-pointer-arithmetic)\n\n\tvoid output_model() {\n\t\tauto& cu_dev = Cuda::ref_cuda_context(gpuid);\n\t\tCudaTimer timer {cu_dev.stream_compute()};\n\n\t\ttimer.tick();\n\n\t\tfor(int i = 0; i < get_model_count(); ++i) {\n\t\t\tint particle_count\t = 0;\n\t\t\tint* d_particle_count = static_cast(cu_dev.borrow(sizeof(int)));\n\n\t\t\t//Init particle count with 0\n\t\t\tcheck_cuda_errors(cudaMemsetAsync(d_particle_count, 0, sizeof(int), cu_dev.stream_compute()));\n\n\t\t\t//Copy particle data to output buffer\n\t\t\tmatch(particle_bins[rollid][i])([this, &cu_dev, &i, &d_particle_count](const auto& particle_buffer) {\n\t\t\t\t//partition_block_count; G_PARTICLE_BATCH_CAPACITY\n\t\t\t\tcu_dev.compute_launch({partition_block_count, config::G_PARTICLE_BATCH_CAPACITY}, retrieve_particle_buffer, partitions[rollid], partitions[(rollid + 1) % BIN_COUNT], particle_buffer, get>(particle_bins[(rollid + 1) % BIN_COUNT][i]), particles[i], d_particle_count);\n\t\t\t});\n\n\t\t\t//Retrieve particle count\n\t\t\tcheck_cuda_errors(cudaMemcpyAsync(&particle_count, d_particle_count, sizeof(int), cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\t\tcu_dev.syncStream();\n\n\t\t\tfmt::print(fg(fmt::color::red), \"total number of particles {}\\n\", particle_count);\n\n\t\t\t//Resize the output model\n\t\t\tmodel.resize(particle_count);\n\n\t\t\t//Copy the data to the output model\n\t\t\tcheck_cuda_errors(cudaMemcpyAsync(model.data(), static_cast(&particles[i].val_1d(_0, 0)), sizeof(std::array) * (particle_count), cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\t\tcu_dev.syncStream();\n\n\t\t\tstd::string fn = std::string {\"model\"} + \"_id[\" + std::to_string(i) + \"]_frame[\" + std::to_string(cur_frame) + \"].bgeo\";\n\n\t\t\t//Write back file\n\t\t\tIO::insert_job([fn, m = model]() {\n\t\t\t\twrite_partio(fn, m);\n\t\t\t});\n\t\t}\n\t\ttimer.tock(fmt::format(\"GPU[{}] frame {} step {} retrieve_particles\", gpuid, cur_frame, cur_step));\n\t}\n\n\t//NOLINTBEGIN(cppcoreguidelines-pro-bounds-pointer-arithmetic)Current c++ version does not yet support std::span\n\tvoid initial_setup() {\n\t\t{\n\t\t\t//TODO: Verify bounds when model offset is too large\n\n\t\t\tauto& cu_dev = Cuda::ref_cuda_context(gpuid);\n\t\t\tCudaTimer timer {cu_dev.stream_compute()};\n\n\t\t\ttimer.tick();\n\n\t\t\t//Activate blocks that contain particles\n\t\t\tfor(int i = 0; i < get_model_count(); ++i) {\n\t\t\t\t//floor(particle_counts[i]/DEFAULT_CUDA_BLOCK_SIZE); DEFAULT_CUDA_BLOCK_SIZE\n\t\t\t\tcu_dev.compute_launch({(particle_counts[i] + DEFAULT_CUDA_BLOCK_SIZE - 1) / DEFAULT_CUDA_BLOCK_SIZE, DEFAULT_CUDA_BLOCK_SIZE}, activate_blocks, particle_counts[i], particles[i], partitions[(rollid + 1) % BIN_COUNT]);\n\t\t\t}\n\n\t\t\t//Store count of activated blocks\n\t\t\tcheck_cuda_errors(cudaMemcpyAsync(&partition_block_count, partitions[(rollid + 1) % BIN_COUNT].count, sizeof(int), cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\t\ttimer.tock(fmt::format(\"GPU[{}] step {} init_table\", gpuid, cur_step));\n\n\t\t\ttimer.tick();\n\t\t\tcu_dev.reset_mem();\n\n\t\t\t//Store particle ids in block cells\n\t\t\tfor(int i = 0; i < get_model_count(); ++i) {\n\t\t\t\tmatch(particle_bins[rollid][i])([this, &cu_dev, &i](auto& particle_buffer) {\n\t\t\t\t\t//floor(particle_counts[i]/DEFAULT_CUDA_BLOCK_SIZE); DEFAULT_CUDA_BLOCK_SIZE\n\t\t\t\t\tcu_dev.compute_launch({(particle_counts[i] + DEFAULT_CUDA_BLOCK_SIZE - 1) / DEFAULT_CUDA_BLOCK_SIZE, DEFAULT_CUDA_BLOCK_SIZE}, build_particle_cell_buckets, particle_counts[i], particles[i], particle_buffer, partitions[(rollid + 1) % BIN_COUNT]);\n\t\t\t\t});\n\t\t\t}\n\t\t\tcu_dev.syncStream();\n\n\t\t\t//Check size\n\t\t\tif(partition_block_count > config::G_MAX_ACTIVE_BLOCK) {\n\t\t\t\tstd::cerr << \"Too much active blocks: \" << partition_block_count << std::endl;\n\t\t\t\tstd::abort();\n\t\t\t}\n\n\t\t\t//Copy cell buckets from partition to particle buffer\n\t\t\tfor(int i = 0; i < get_model_count(); ++i) {\n\t\t\t\tmatch(particle_bins[rollid][i])([this, &cu_dev](auto& particle_buffer) {\n\t\t\t\t\t//First init sizes with 0\n\t\t\t\t\tcheck_cuda_errors(cudaMemsetAsync(particle_buffer.particle_bucket_sizes, 0, sizeof(int) * (partition_block_count + 1), cu_dev.stream_compute()));\n\n\t\t\t\t\t//partition_block_count; G_BLOCKVOLUME\n\t\t\t\t\tcu_dev.compute_launch({partition_block_count, config::G_BLOCKVOLUME}, cell_bucket_to_block, particle_buffer.cell_particle_counts, particle_buffer.cellbuckets, particle_buffer.particle_bucket_sizes, particle_buffer.blockbuckets);\n\t\t\t\t\t// partitions[(rollid + 1)%BIN_COUNT].buildParticleBuckets(cu_dev, partition_block_count);\n\t\t\t\t});\n\t\t\t}\n\n\t\t\t//Compute bin capacities, bin offsets and the summed bin size\n\t\t\t//Then initializes the particle buffer\n\t\t\tint* bin_sizes = tmps.bin_sizes;\n\t\t\tfor(int i = 0; i < get_model_count(); ++i) {\n\t\t\t\tmatch(particle_bins[rollid][i])([this, &cu_dev, &bin_sizes, &i](auto& particle_buffer) {\n\t\t\t\t\t//floor((partition_block_count + 1)/G_PARTICLE_BATCH_CAPACITY); G_PARTICLE_BATCH_CAPACITY\n\t\t\t\t\tcu_dev.compute_launch({partition_block_count / config::G_PARTICLE_BATCH_CAPACITY + 1, config::G_PARTICLE_BATCH_CAPACITY}, compute_bin_capacity, partition_block_count + 1, static_cast(particle_buffer.particle_bucket_sizes), bin_sizes);\n\n\t\t\t\t\t//Stores aggregated bin sizes in particle_buffer\n\t\t\t\t\texclusive_scan(partition_block_count + 1, bin_sizes, particle_buffer.bin_offsets, cu_dev);\n\n\t\t\t\t\t//Stores last aggregated size == whole size in bincount\n\t\t\t\t\tcheck_cuda_errors(cudaMemcpyAsync(&bincount[i], particle_buffer.bin_offsets + partition_block_count, sizeof(int), cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\t\t\t\tcu_dev.syncStream();\n\n\t\t\t\t\t//Initialize particle buffer\n\t\t\t\t\t//partition_block_count; G_PARTICLE_BATCH_CAPACITY\n\t\t\t\t\tcu_dev.compute_launch({partition_block_count, config::G_PARTICLE_BATCH_CAPACITY}, array_to_buffer, particles[i], particle_buffer);\n\t\t\t\t});\n\t\t\t}\n\n\t\t\t//Activate blocks near active blocks\n\t\t\t//floor(partition_block_count/G_PARTICLE_BATCH_CAPACITY); G_PARTICLE_BATCH_CAPACITY\n\t\t\tcu_dev.compute_launch({(partition_block_count + config::G_PARTICLE_BATCH_CAPACITY - 1) / config::G_PARTICLE_BATCH_CAPACITY, config::G_PARTICLE_BATCH_CAPACITY}, register_neighbor_blocks, static_cast(partition_block_count), partitions[(rollid + 1) % BIN_COUNT]);\n\n\t\t\t//Retrieve total count\n\t\t\tcheck_cuda_errors(cudaMemcpyAsync(&neighbor_block_count, partitions[(rollid + 1) % BIN_COUNT].count, sizeof(int), cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\t\tcu_dev.syncStream();\n\n\t\t\t//Check size\n\t\t\tif(neighbor_block_count > config::G_MAX_ACTIVE_BLOCK) {\n\t\t\t\tstd::cerr << \"Too much neighbour blocks: \" << partition_block_count << std::endl;\n\t\t\t\tstd::abort();\n\t\t\t}\n\n\t\t\t//Activate blocks near active blocks, including those before that block\n\t\t\t//TODO: Only these with offset -1 are not already activated as neighbours\n\t\t\t//floor(partition_block_count/G_PARTICLE_BATCH_CAPACITY); G_PARTICLE_BATCH_CAPACITY\n\t\t\tcu_dev.compute_launch({(partition_block_count + config::G_PARTICLE_BATCH_CAPACITY - 1) / config::G_PARTICLE_BATCH_CAPACITY, config::G_PARTICLE_BATCH_CAPACITY}, register_exterior_blocks, static_cast(partition_block_count), partitions[(rollid + 1) % BIN_COUNT]);\n\n\t\t\t//Retrieve total count\n\t\t\tcheck_cuda_errors(cudaMemcpyAsync(&exterior_block_count, partitions[(rollid + 1) % BIN_COUNT].count, sizeof(int), cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\t\tcu_dev.syncStream();\n\n\t\t\t//Check size\n\t\t\tif(exterior_block_count > config::G_MAX_ACTIVE_BLOCK) {\n\t\t\t\tstd::cerr << \"Too much exterior blocks: \" << partition_block_count << std::endl;\n\t\t\t\tstd::abort();\n\t\t\t}\n\n\t\t\ttimer.tock(fmt::format(\"GPU[{}] step {} init_partition\", gpuid, cur_step));\n\n\t\t\tfmt::print(fmt::emphasis::bold | fg(fmt::color::yellow), \"block count on device {}: {}, {}, {} [{}]\\n\", gpuid, partition_block_count, neighbor_block_count, exterior_block_count, cur_num_active_blocks);\n\t\t\tfor(int i = 0; i < get_model_count(); ++i) {\n\t\t\t\tfmt::print(fmt::emphasis::bold | fg(fmt::color::yellow), \"bin count on device {}: model {}: {} [{}]\\n\", gpuid, i, bincount[i], cur_num_active_bins[i]);\n\t\t\t}\n\t\t}\n\n\t\t{\n\t\t\tauto& cu_dev = Cuda::ref_cuda_context(gpuid);\n\t\t\tCudaTimer timer {cu_dev.stream_compute()};\n\n\t\t\t//Copy all blocks to background partition\n\t\t\tpartitions[(rollid + 1) % BIN_COUNT].copy_to(partitions[rollid], exterior_block_count, cu_dev.stream_compute());\n\t\t\tcheck_cuda_errors(cudaMemcpyAsync(partitions[rollid].active_keys, partitions[(rollid + 1) % BIN_COUNT].active_keys, sizeof(ivec3) * exterior_block_count, cudaMemcpyDefault, cu_dev.stream_compute()));\n\n\t\t\t//Copy all particle data to background particle buffer\n\t\t\tfor(int i = 0; i < get_model_count(); ++i) {\n\t\t\t\tmatch(particle_bins[rollid][i])([this, &cu_dev, &i](const auto& particle_buffer) {\n\t\t\t\t\t// bin_offsets, particle_bucket_sizes\n\t\t\t\t\tparticle_buffer.copy_to(get>(particle_bins[(rollid + 1) % BIN_COUNT][i]), partition_block_count, cu_dev.stream_compute());\n\t\t\t\t});\n\t\t\t}\n\t\t\tcu_dev.syncStream();\n\n\t\t\ttimer.tick();\n\n\t\t\t//Clear the grid\n\t\t\tgrid_blocks[0].reset(neighbor_block_count, cu_dev);\n\n\t\t\t//Initialize the grid and advection buckets\n\t\t\tfor(int i = 0; i < get_model_count(); ++i) {\n\t\t\t\t//Initialize mass and momentum\n\t\t\t\t//floor(particle_counts[i]/DEFAULT_CUDA_BLOCK_SIZE); DEFAULT_CUDA_BLOCK_SIZE\n\t\t\t\tcu_dev.compute_launch({(particle_counts[i] + DEFAULT_CUDA_BLOCK_SIZE - 1) / DEFAULT_CUDA_BLOCK_SIZE, DEFAULT_CUDA_BLOCK_SIZE}, rasterize, particle_counts[i], particles[i], grid_blocks[0], partitions[rollid], dt, get_mass(i), vel0[i].data_arr());\n\n\t\t\t\t//Init advection source at offset 0 of destination\n\t\t\t\tmatch(particle_bins[(rollid + 1) % BIN_COUNT][i])([this, &cu_dev](auto& particle_buffer) {\n\t\t\t\t\t//partition_block_count; G_PARTICLE_BATCH_CAPACITY\n\t\t\t\t\tcu_dev.compute_launch({partition_block_count, config::G_PARTICLE_BATCH_CAPACITY}, init_adv_bucket, static_cast(particle_buffer.particle_bucket_sizes), particle_buffer.blockbuckets);\n\t\t\t\t});\n\t\t\t}\n\t\t\tcu_dev.syncStream();\n\t\t\ttimer.tock(fmt::format(\"GPU[{}] step {} init_grid\", gpuid, cur_step));\n\t\t}\n\t}\n\t//NOLINTEND(cppcoreguidelines-pro-bounds-pointer-arithmetic)\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Projects/GMPM/grid_buffer.cuh", "content": "#ifndef GRID_BUFFER_CUH\n#define GRID_BUFFER_CUH\n#include \n\n#include \"mgmpm_kernels.cuh\"\n#include \"settings.h\"\n\nnamespace mn {\nusing namespace placeholder;//NOLINT(google-build-using-namespace) Allow placeholders to be included generally for simplification\n\n//NOLINTBEGIN(cppcoreguidelines-avoid-non-const-global-variables, readability-identifier-naming) Check is buggy and reporst variable errors fro template arguments\nusing grid_block_ = Structural, BlockDomain, attrib_layout::SOA, f32_, f32_, f32_, f32_>;\nusing grid_\t\t = Structural, GridDomain, attrib_layout::AOS, grid_block_>;\nusing grid_buffer_ = Structural, GridBufferDomain, attrib_layout::AOS, grid_block_>;\n//NOLINTEND(cppcoreguidelines-avoid-non-const-global-variables, readability-identifier-naming)\n\nstruct GridBuffer : Instance {\n\tusing base_t = Instance;\n\n\ttemplate\n\texplicit GridBuffer(Allocator allocator)\n\t\t: base_t {spawn(allocator)} {}\n\n\ttemplate\n\tvoid check_capacity(Allocator allocator, std::size_t capacity) {\n\t\tif(capacity > this->capacity) {\n\t\t\tthis->resize(allocator, capacity);\n\t\t}\n\t}\n\n\ttemplate\n\tvoid reset(int block_count, CudaContext& cu_dev) {\n\t\t//check_cuda_errors(cudaMemsetAsync((void *)&this->val_1d(_0, 0), 0, grid_block_::size * block_count, cu_dev.stream_compute()));\n\t\tcu_dev.compute_launch({block_count, config::G_BLOCKVOLUME}, clear_grid, *this);\n\t}\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Projects/GMPM/hash_table.cuh", "content": "#ifndef HASH_TABLE_CUH\n#define HASH_TABLE_CUH\n#include \n\n#include \n\n#include \"settings.h\"\n\nnamespace mn {\n\ntemplate\nstruct HaloPartition {\n\ttemplate\n\tHaloPartition(Allocator allocator, int max_block_count) {\n\t\t(void) allocator;\n\t\t(void) max_block_count;\n\t}\n\n\ttemplate\n\tvoid resize_partition(Allocator allocator, std::size_t prev_capacity, std::size_t capacity) {}\n\tvoid copy_to(HaloPartition& other, std::size_t block_count, cudaStream_t stream) {}\n};\ntemplate<>\nstruct HaloPartition<1> {\n\tint* halo_count;\n\tint h_count;\n\tchar* halo_marks;///< halo particle blocks\n\tint* overlap_marks;\n\tivec3* halo_blocks;\n\n\ttemplate\n\tHaloPartition(Allocator allocator, int max_block_count)\n\t\t: h_count(0) {\n\t\thalo_count\t = static_cast(allocator.allocate(sizeof(char) * max_block_count));\n\t\thalo_marks\t = static_cast(allocator.allocate(sizeof(char) * max_block_count));\n\t\toverlap_marks = static_cast(allocator.allocate(sizeof(int) * max_block_count));\n\t\thalo_blocks\t = static_cast(allocator.allocate(sizeof(ivec3) * max_block_count));\n\t}\n\n\tvoid copy_to(HaloPartition& other, std::size_t block_count, cudaStream_t stream) const {\n\t\tother.h_count = h_count;\n\t\tcheck_cuda_errors(cudaMemcpyAsync(other.halo_marks, halo_marks, sizeof(char) * block_count, cudaMemcpyDefault, stream));\n\t\tcheck_cuda_errors(cudaMemcpyAsync(other.overlap_marks, overlap_marks, sizeof(int) * block_count, cudaMemcpyDefault, stream));\n\t\tcheck_cuda_errors(cudaMemcpyAsync(other.halo_blocks, halo_blocks, sizeof(ivec3) * block_count, cudaMemcpyDefault, stream));\n\t}\n\n\ttemplate\n\tvoid resize_partition(Allocator allocator, std::size_t prev_capacity, std::size_t capacity) {\n\t\tallocator.deallocate(halo_marks, sizeof(char) * prev_capacity);\n\t\tallocator.deallocate(overlap_marks, sizeof(int) * prev_capacity);\n\t\tallocator.deallocate(halo_blocks, sizeof(ivec3) * prev_capacity);\n\t\thalo_marks\t = static_cast(allocator.allocate(sizeof(char) * capacity));\n\t\toverlap_marks = static_cast(allocator.allocate(sizeof(int) * capacity));\n\t\thalo_blocks\t = static_cast(allocator.allocate(sizeof(ivec3) * capacity));\n\t}\n\n\tvoid reset_halo_count(cudaStream_t stream) const {\n\t\tcheck_cuda_errors(cudaMemsetAsync(halo_count, 0, sizeof(int), stream));\n\t}\n\n\tvoid reset_overlap_marks(uint32_t neighbor_block_count, cudaStream_t stream) const {\n\t\tcheck_cuda_errors(cudaMemsetAsync(overlap_marks, 0, sizeof(int) * neighbor_block_count, stream));\n\t}\n\n\tvoid retrieve_halo_count(cudaStream_t stream) {\n\t\tcheck_cuda_errors(cudaMemcpyAsync(&h_count, halo_count, sizeof(int), cudaMemcpyDefault, stream));\n\t}\n};\n\n//NOLINTBEGIN(cppcoreguidelines-avoid-non-const-global-variables, readability-identifier-naming) Check is buggy and reporst variable errors fro template arguments\nusing block_partition_ = Structural, GridDomain, attrib_layout::AOS, empty_>;\n//NOLINTEND(cppcoreguidelines-avoid-non-const-global-variables, readability-identifier-naming)\n\n//NOLINTBEGIN(cppcoreguidelines-pro-bounds-pointer-arithmetic) Using pointer arithmetics cause library and allocators do so.\ntemplate\nstruct Partition\n\t: Instance\n\t, HaloPartition {\n\tusing base_t\t = Instance;\n\tusing halo_base_t = HaloPartition;\n\tusing block_partition_::key_t;\n\tusing block_partition_::value_t;\n\tstatic_assert(sentinel_v == (value_t) (-1), \"sentinel value not full 1s\\n\");\n\n\ttemplate\n\tPartition(Allocator allocator, int max_block_count)\n\t\t: halo_base_t {allocator, max_block_count} {\n\t\tallocate_table(allocator, max_block_count);\n\t\t/// init\n\t\treset();\n\t}\n\n\t~Partition() = default;\n\n\tPartition(const Partition& other)\t\t\t\t = default;\n\tPartition(Partition&& other) noexcept\t\t\t = default;\n\tPartition& operator=(const Partition& other)\t = default;\n\tPartition& operator=(Partition&& other) noexcept = default;\n\n\ttemplate\n\tvoid resize_partition(Allocator allocator, std::size_t capacity) {\n\t\thalo_base_t::resize_partition(allocator, this->capacity, capacity);\n\t\tresize_table(allocator, capacity);\n\t}\n\n\tvoid reset() {\n\t\tcheck_cuda_errors(cudaMemset(this->Instance::count, 0, sizeof(value_t)));\n\t\tcheck_cuda_errors(cudaMemset(this->index_table, 0xff, sizeof(value_t) * domain::extent));\n\t}\n\tvoid reset_table(cudaStream_t stream) {\n\t\tcheck_cuda_errors(cudaMemsetAsync(this->index_table, 0xff, sizeof(value_t) * domain::extent, stream));\n\t}\n\tvoid copy_to(Partition& other, std::size_t block_count, cudaStream_t stream) {\n\t\thalo_base_t::copy_to(other, block_count, stream);\n\t\tcheck_cuda_errors(cudaMemcpyAsync(other.index_table, this->index_table, sizeof(value_t) * domain::extent, cudaMemcpyDefault, stream));\n\t}\n\t//FIXME: passing kjey_t here might cause problems because cuda is buggy\n\t__forceinline__ __device__ value_t insert(key_t key) noexcept {\n\t\tvalue_t tag = atomicCAS(&this->index(key), sentinel_v, 0);\n\t\tif(tag == sentinel_v) {\n\t\t\tvalue_t idx\t\t\t = atomicAdd(this->Instance::count, 1);\n\t\t\tthis->index(key)\t = idx;\n\t\t\tthis->active_keys[idx] = key;///< created a record\n\t\t\treturn idx;\n\t\t}\n\t\treturn -1;\n\t}\n\t//FIXME: passing kjey_t here might cause problems because cuda is buggy\n\t__forceinline__ __device__ value_t query(key_t key) const noexcept {\n\t\treturn this->index(key);\n\t}\n\t__forceinline__ __device__ void reinsert(value_t index) {\n\t\tthis->index(this->active_keys[index]) = index;\n\t}\n};\n//NOLINTEND(cppcoreguidelines-pro-bounds-pointer-arithmetic)\n\n}// namespace mn\n\n#endif" }, { "path": "Projects/GMPM/mgmpm_kernels.cuh", "content": "#ifndef MULTI_GMPM_KERNELS_CUH\n#define MULTI_GMPM_KERNELS_CUH\n\n#include \n\n#include \n#include \n\n#include \"constitutive_models.cuh\"\n#include \"particle_buffer.cuh\"\n#include \"settings.h\"\n#include \"utility_funcs.hpp\"\n\nnamespace mn {\nusing namespace placeholder;//NOLINT(google-build-using-namespace) Allow placeholders to be included generally for simplification\n\n//TODO: Make magic numbers to constants where suitable\n//TODO: Ensure call dimensions and such are small enough to allow narrowing conversations. Or directly use unsigned where possible\n//TODO: Maybe use names instead of formula signs for better understanding\n//NOLINTBEGIN(cppcoreguidelines-pro-bounds-pointer-arithmetic, readability-magic-numbers, readability-identifier-naming, misc-definitions-in-headers) CUDA does not yet support std::span; Common names for physical formulas; Cannot declare __global__ functions inline\ntemplate\n__global__ void activate_blocks(uint32_t particle_counts, ParticleArray particle_array, Partition partition) {\n\tconst uint32_t particle_id = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(particle_id >= particle_counts) {\n\t\treturn;\n\t}\n\n\t//Get block id by particle pos\n\tconst ivec3 coord\t= get_block_id({particle_array.val(_0, particle_id), particle_array.val(_1, particle_id), particle_array.val(_2, particle_id)}) - 2;\n\tconst ivec3 blockid = coord / static_cast(config::G_BLOCKSIZE);\n\n\t//Create block in partition\n\tpartition.insert(blockid);\n}\n\ntemplate\n__global__ void build_particle_cell_buckets(uint32_t particle_counts, ParticleArray particle_array, ParticleBuffer particle_buffer, Partition partition) {\n\tconst uint32_t particle_id = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(particle_id >= particle_counts) {\n\t\treturn;\n\t}\n\n\t//Get block id by particle pos\n\tconst ivec3 coord\t= get_block_id({particle_array.val(_0, particle_id), particle_array.val(_1, particle_id), particle_array.val(_2, particle_id)}) - 2;\n\tconst ivec3 blockid = coord / static_cast(config::G_BLOCKSIZE);\n\n\t//Fetch block number\n\tauto blockno = partition.query(blockid);\n\n\t//Get cell number in block\n\tint cellno = (coord[0] & config::G_BLOCKMASK) * config::G_BLOCKSIZE * config::G_BLOCKSIZE + (coord[1] & config::G_BLOCKMASK) * config::G_BLOCKSIZE + (coord[2] & config::G_BLOCKMASK);\n\n\t//Increase particle count of cell and get id of partzicle in cell\n\tauto particle_id_in_cell = atomicAdd(particle_buffer.cell_particle_counts + blockno * config::G_BLOCKVOLUME + cellno, 1);\n\n\t//If no space is left, don't store the particle\n\tif(particle_id_in_cell >= config::G_MAX_PARTICLES_IN_CELL) {\n\t\t//Reduce count again\n\t\tatomicSub(particle_buffer.cell_particle_counts + blockno * config::G_BLOCKVOLUME + cellno, 1);\n#if PRINT_CELL_OVERFLOW\n\t\tprintf(\"No space left in cell: block(%d), cell(%d)\\n\", blockno, cellno);\n#endif\n\t\treturn;\n\t}\n\n\t//Insert particle id in cell bucket\n\tparticle_buffer.cellbuckets[blockno * config::G_PARTICLE_NUM_PER_BLOCK + cellno * config::G_MAX_PARTICLES_IN_CELL + particle_id_in_cell] = static_cast(particle_id);//NOTE:Explicit narrowing conversation.\n}\n\n__global__ void cell_bucket_to_block(const int* cell_particle_counts, const int* cellbuckets, int* particle_bucket_sizes, int* buckets) {\n\tconst int cellno\t\t = static_cast(threadIdx.x) & (config::G_BLOCKVOLUME - 1);\n\tconst int particle_counts = cell_particle_counts[blockIdx.x * config::G_BLOCKVOLUME + cellno];\n\n\tfor(int particle_id_in_cell = 0; particle_id_in_cell < config::G_MAX_PARTICLES_IN_CELL; particle_id_in_cell++) {\n\t\tif(particle_id_in_cell < particle_counts) {\n\t\t\t//Each thread gets its index in the blocks bucket\n\t\t\tconst int particle_id_in_block = atomic_agg_inc(particle_bucket_sizes + blockIdx.x);\n\n\t\t\t//Each particle of the source advection buffer (offset + particle id) is assigned to a particle of the current buffer. This should be a 1:1 mapping, though one particle may be mapped to itself or to another particle\n\t\t\tbuckets[blockIdx.x * config::G_PARTICLE_NUM_PER_BLOCK + particle_id_in_block] = cellbuckets[blockIdx.x * config::G_PARTICLE_NUM_PER_BLOCK + cellno * config::G_MAX_PARTICLES_IN_CELL + particle_id_in_cell];\n\t\t}\n\t\t__syncthreads();\n\t}\n}\n\n__global__ void compute_bin_capacity(uint32_t block_count, int const* particle_bucket_sizes, int* bin_sizes) {\n\tconst uint32_t blockno = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(blockno >= block_count) {\n\t\treturn;\n\t}\n\n\t//Bin capacity is the ceiled bucket size divided by the bin max capacity\n\tbin_sizes[blockno] = (particle_bucket_sizes[blockno] + config::G_BIN_CAPACITY - 1) / config::G_BIN_CAPACITY;\n}\n\n__global__ void init_adv_bucket(const int* particle_bucket_sizes, int* buckets) {\n\tconst int particle_counts = particle_bucket_sizes[blockIdx.x];\n\tint* bucket\t\t\t\t = buckets + static_cast(blockIdx.x) * config::G_PARTICLE_NUM_PER_BLOCK;\n\n\tfor(int particle_id_in_block = static_cast(threadIdx.x); particle_id_in_block < particle_counts; particle_id_in_block += static_cast(blockDim.x)) {\n\t\t//Combine offset of 0 with local index in block\n\t\tbucket[particle_id_in_block] = (dir_offset({0, 0, 0}) * config::G_PARTICLE_NUM_PER_BLOCK) | particle_id_in_block;\n\t}\n}\n\ntemplate\n__global__ void clear_grid(Grid grid) {\n\tauto gridblock = grid.ch(_0, blockIdx.x);\n\tfor(int cell_id_in_block = static_cast(threadIdx.x); cell_id_in_block < config::G_BLOCKVOLUME; cell_id_in_block += static_cast(blockDim.x)) {\n\t\tgridblock.val_1d(_0, cell_id_in_block) = 0.0f;\n\t\tgridblock.val_1d(_1, cell_id_in_block) = 0.0f;\n\t\tgridblock.val_1d(_2, cell_id_in_block) = 0.0f;\n\t\tgridblock.val_1d(_3, cell_id_in_block) = 0.0f;\n\t}\n}\n\ntemplate\n__global__ void register_neighbor_blocks(uint32_t block_count, Partition partition) {\n\tconst uint32_t blockno = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(blockno >= block_count) {\n\t\treturn;\n\t}\n\n\t//Activate neighbour blocks\n\tconst auto blockid = partition.active_keys[blockno];\n\tfor(char i = 0; i < 2; ++i) {\n\t\tfor(char j = 0; j < 2; ++j) {\n\t\t\tfor(char k = 0; k < 2; ++k) {\n\t\t\t\tpartition.insert(ivec3 {blockid[0] + i, blockid[1] + j, blockid[2] + k});\n\t\t\t}\n\t\t}\n\t}\n}\n\ntemplate\n__global__ void register_exterior_blocks(uint32_t block_count, Partition partition) {\n\tconst uint32_t blockno = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(blockno >= block_count) {\n\t\treturn;\n\t}\n\n\t//Activate exterior blocks\n\tconst auto blockid = partition.active_keys[blockno];\n\tfor(char i = -1; i < 2; ++i) {\n\t\tfor(char j = -1; j < 2; ++j) {\n\t\t\tfor(char k = -1; k < 2; ++k) {\n\t\t\t\tpartition.insert(ivec3 {blockid[0] + i, blockid[1] + j, blockid[2] + k});\n\t\t\t}\n\t\t}\n\t}\n}\n\ntemplate\n__global__ void rasterize(uint32_t particle_counts, const ParticleArray particle_array, Grid grid, const Partition partition, Duration dt, float mass, std::array v0) {\n\t(void) dt;\n\n\tconst uint32_t particle_id = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(particle_id >= particle_counts) {\n\t\treturn;\n\t}\n\n\t//Fetch particle position and velocity\n\tconst vec3 global_pos {particle_array.val(_0, particle_id), particle_array.val(_1, particle_id), particle_array.val(_2, particle_id)};\n\tconst vec3 vel {v0[0], v0[1], v0[2]};\n\n\t//vec9 contrib;\n\t//vec9 c;\n\t//contrib.set(0.f);\n\t//c.set(0.f);\n\n\t//contrib = (c * mass - contrib * dt.count()) * config::G_D_INV;\n\n\t//Calculate grid index\n\tconst ivec3 global_base_index = get_block_id(global_pos.data_arr()) - 1;\n\n\t//Calculate position relative to grid cell\n\tconst vec3 local_pos = global_pos - global_base_index * config::G_DX;\n\n\t//Calc kernel\n\tvec dws;\n\tfor(int d = 0; d < 3; ++d) {\n\t\tdws[d] = bspline_weight(local_pos[d]);\n\t}\n\n\tfor(int i = 0; i < 3; ++i) {\n\t\tfor(int j = 0; j < 3; ++j) {\n\t\t\tfor(int k = 0; k < 3; ++k) {\n\t\t\t\t//Current offset from grid cell\n\t\t\t\tconst ivec3 offset {i, j, k};\n\n\t\t\t\t//Global index of grid cell\n\t\t\t\tconst ivec3 global_index = global_base_index + offset;\n\n\t\t\t\tivec3 global_index_masked;\n\t\t\t\tfor(int d = 0; d < 3; ++d) {\n\t\t\t\t\tglobal_index_masked[d] = global_index[d] & config::G_BLOCKMASK;\n\t\t\t\t}\n\n\t\t\t\t//const vec3 xixp\t\t = offset * config::G_DX - local_pos;\n\n\t\t\t\t//Kernel weight\n\t\t\t\tconst float w = dws[0][i] * dws[1][j] * dws[2][k];\n\n\t\t\t\t//Mass constribution to the grid cell\n\t\t\t\tconst float wm = mass * w;\n\n\t\t\t\t//Fetch block number\n\t\t\t\tconst int blockno = partition.query(ivec3 {static_cast(global_index[0] >> config::G_BLOCKBITS), static_cast(global_index[1] >> config::G_BLOCKBITS), static_cast(global_index[2] >> config::G_BLOCKBITS)});\n\n\t\t\t\t//Fetch grid block and initialize values\n\t\t\t\tauto grid_block = grid.ch(_0, blockno);\n\t\t\t\tatomicAdd(&grid_block.val(_0, global_index_masked[0], global_index_masked[1], global_index_masked[2]), wm);\n\t\t\t\tatomicAdd(&grid_block.val(_1, global_index_masked[0], global_index_masked[1], global_index_masked[2]), wm * vel[0]);// + (contrib[0] * xixp[0] + contrib[3] * xixp[1] + contrib[6] * xixp[2]) * w);\n\t\t\t\tatomicAdd(&grid_block.val(_2, global_index_masked[0], global_index_masked[1], global_index_masked[2]), wm * vel[1]);// + (contrib[1] * xixp[0] + contrib[4] * xixp[1] + contrib[7] * xixp[2]) * w);\n\t\t\t\tatomicAdd(&grid_block.val(_3, global_index_masked[0], global_index_masked[1], global_index_masked[2]), wm * vel[2]);// + (contrib[2] * xixp[0] + contrib[5] * xixp[1] + contrib[8] * xixp[2]) * w);\n\t\t\t}\n\t\t}\n\t}\n}\n\ntemplate\n__global__ void array_to_buffer(ParticleArray particle_array, ParticleBuffer particle_buffer) {\n\tconst uint32_t blockno\t = blockIdx.x;\n\tconst int particle_counts = particle_buffer.particle_bucket_sizes[blockno];\n\tconst int* bucket\t\t = particle_buffer.blockbuckets + static_cast(blockno) * config::G_PARTICLE_NUM_PER_BLOCK;\n\n\tfor(int particle_id_in_block = static_cast(threadIdx.x); particle_id_in_block < particle_counts; particle_id_in_block += static_cast(blockDim.x)) {\n\t\tconst int particle_id = bucket[particle_id_in_block];\n\n\t\tauto particle_bin = particle_buffer.ch(_0, particle_buffer.bin_offsets[blockno] + particle_id_in_block / config::G_BIN_CAPACITY);\n\t\t/// pos\n\t\tparticle_bin.val(_0, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_0, particle_id);\n\t\tparticle_bin.val(_1, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_1, particle_id);\n\t\tparticle_bin.val(_2, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_2, particle_id);\n\t\t/// J\n\t\tparticle_bin.val(_3, particle_id_in_block % config::G_BIN_CAPACITY) = 1.0f;\n\t}\n}\n\ntemplate\n__global__ void array_to_buffer(ParticleArray particle_array, ParticleBuffer particle_buffer) {\n\tconst uint32_t blockno\t = blockIdx.x;\n\tconst int particle_counts = particle_buffer.particle_bucket_sizes[blockno];\n\tconst int* bucket\t\t = particle_buffer.blockbuckets + static_cast(blockno) * config::G_PARTICLE_NUM_PER_BLOCK;\n\n\tfor(int particle_id_in_block = static_cast(threadIdx.x); particle_id_in_block < particle_counts; particle_id_in_block += static_cast(blockDim.x)) {\n\t\tconst auto particle_id = bucket[particle_id_in_block];\n\n\t\tauto particle_bin = particle_buffer.ch(_0, particle_buffer.bin_offsets[blockno] + particle_id_in_block / config::G_BIN_CAPACITY);\n\t\t/// pos\n\t\tparticle_bin.val(_0, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_0, particle_id);\n\t\tparticle_bin.val(_1, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_1, particle_id);\n\t\tparticle_bin.val(_2, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_2, particle_id);\n\t\t/// F\n\t\tparticle_bin.val(_3, particle_id_in_block % config::G_BIN_CAPACITY)\t = 1.f;\n\t\tparticle_bin.val(_4, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_5, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_6, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_7, particle_id_in_block % config::G_BIN_CAPACITY)\t = 1.f;\n\t\tparticle_bin.val(_8, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_9, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_10, particle_id_in_block % config::G_BIN_CAPACITY) = 0.f;\n\t\tparticle_bin.val(_11, particle_id_in_block % config::G_BIN_CAPACITY) = 1.f;\n\t}\n}\n\ntemplate\n__global__ void array_to_buffer(ParticleArray particle_array, ParticleBuffer particle_buffer) {\n\tconst uint32_t blockno\t = blockIdx.x;\n\tconst int particle_counts = particle_buffer.particle_bucket_sizes[blockno];\n\tconst int* bucket\t\t = particle_buffer.blockbuckets + static_cast(blockno) * config::G_PARTICLE_NUM_PER_BLOCK;\n\n\tfor(int particle_id_in_block = static_cast(threadIdx.x); particle_id_in_block < particle_counts; particle_id_in_block += static_cast(blockDim.x)) {\n\t\tconst auto particle_id = bucket[particle_id_in_block];\n\n\t\tauto particle_bin = particle_buffer.ch(_0, particle_buffer.bin_offsets[blockno] + particle_id_in_block / config::G_BIN_CAPACITY);\n\t\t/// pos\n\t\tparticle_bin.val(_0, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_0, particle_id);\n\t\tparticle_bin.val(_1, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_1, particle_id);\n\t\tparticle_bin.val(_2, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_2, particle_id);\n\t\t/// F\n\t\tparticle_bin.val(_3, particle_id_in_block % config::G_BIN_CAPACITY)\t = 1.f;\n\t\tparticle_bin.val(_4, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_5, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_6, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_7, particle_id_in_block % config::G_BIN_CAPACITY)\t = 1.f;\n\t\tparticle_bin.val(_8, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_9, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_10, particle_id_in_block % config::G_BIN_CAPACITY) = 0.f;\n\t\tparticle_bin.val(_11, particle_id_in_block % config::G_BIN_CAPACITY) = 1.f;\n\t\t/// log_jp\n\t\tparticle_bin.val(_12, particle_id_in_block % config::G_BIN_CAPACITY) = ParticleBuffer::LOG_JP_0;\n\t}\n}\n\ntemplate\n__global__ void array_to_buffer(ParticleArray particle_array, ParticleBuffer particle_buffer) {\n\tconst uint32_t blockno\t = blockIdx.x;\n\tconst int particle_counts = particle_buffer.particle_bucket_sizes[blockno];\n\tconst int* bucket\t\t = particle_buffer.blockbuckets + static_cast(blockno) * config::G_PARTICLE_NUM_PER_BLOCK;\n\n\tfor(int particle_id_in_block = static_cast(threadIdx.x); particle_id_in_block < particle_counts; particle_id_in_block += static_cast(blockDim.x)) {\n\t\tconst auto particle_id = bucket[particle_id_in_block];\n\n\t\tauto particle_bin = particle_buffer.ch(_0, particle_buffer.bin_offsets[blockno] + particle_id_in_block / config::G_BIN_CAPACITY);\n\t\t/// pos\n\t\tparticle_bin.val(_0, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_0, particle_id);\n\t\tparticle_bin.val(_1, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_1, particle_id);\n\t\tparticle_bin.val(_2, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_2, particle_id);\n\t\t/// F\n\t\tparticle_bin.val(_3, particle_id_in_block % config::G_BIN_CAPACITY)\t = 1.f;\n\t\tparticle_bin.val(_4, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_5, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_6, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_7, particle_id_in_block % config::G_BIN_CAPACITY)\t = 1.f;\n\t\tparticle_bin.val(_8, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_9, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_10, particle_id_in_block % config::G_BIN_CAPACITY) = 0.f;\n\t\tparticle_bin.val(_11, particle_id_in_block % config::G_BIN_CAPACITY) = 1.f;\n\t\t/// log_jp\n\t\tparticle_bin.val(_12, particle_id_in_block % config::G_BIN_CAPACITY) = ParticleBuffer::LOG_JP_0;\n\t}\n}\n\ntemplate\n__global__ void update_grid_velocity_query_max(uint32_t block_count, Grid grid, Partition partition, Duration dt, float* max_vel) {\n\tconst int boundary_condition = static_cast(std::floor(config::G_BOUNDARY_CONDITION));\n\tconstexpr int NUM_WARPS\t\t = config::G_NUM_GRID_BLOCKS_PER_CUDA_BLOCK * config::G_NUM_WARPS_PER_GRID_BLOCK;\n\tconstexpr unsigned ACTIVE_MASK = 0xffffffff;\n\n\tstatic constexpr size_t shared_memory_element_count = NUM_WARPS;\n\t__shared__ float sh_maxvels[shared_memory_element_count];//NOLINT(modernize-avoid-c-arrays) Cannot declare runtime size shared memory as std::array\n\n\t//Fetch block number and id\n\tconst int blockno = static_cast(blockIdx.x) * config::G_NUM_GRID_BLOCKS_PER_CUDA_BLOCK + static_cast(threadIdx.x) / config::CUDA_WARP_SIZE / config::G_NUM_WARPS_PER_GRID_BLOCK;\n\tconst auto blockid = partition.active_keys[blockno];\n\n\t//Check if the block is outside of grid bounds\n\tconst int is_in_bound = ((blockid[0] < boundary_condition || blockid[0] >= config::G_GRID_SIZE - boundary_condition) << 2) | ((blockid[1] < boundary_condition || blockid[1] >= config::G_GRID_SIZE - boundary_condition) << 1) | (blockid[2] < boundary_condition || blockid[2] >= config::G_GRID_SIZE - boundary_condition);\n\n\t//Initialize shared memory\n\tif(threadIdx.x < NUM_WARPS) {\n\t\tsh_maxvels[threadIdx.x] = 0.0f;\n\t}\n\t__syncthreads();\n\n\t/// within-warp computations\n\tif(blockno < block_count) {\n\t\tauto grid_block = grid.ch(_0, blockno);\n\t\tfor(int cell_id_in_block = static_cast(threadIdx.x % config::CUDA_WARP_SIZE); cell_id_in_block < config::G_BLOCKVOLUME; cell_id_in_block += config::CUDA_WARP_SIZE) {\n\t\t\tconst float mass = grid_block.val_1d(_0, cell_id_in_block);\n\t\t\tfloat vel_sqr\t = 0.0f;\n\t\t\tvec3 vel;\n\t\t\tif(mass > 0.0f) {\n\t\t\t\tconst float mass_inv = 1.f / mass;\n\n\t\t\t\t//int i = (cell_id_in_block >> (config::G_BLOCKBITS << 1)) & config::G_BLOCKMASK;\n\t\t\t\t//int j = (cell_id_in_block >> config::G_BLOCKBITS) & config::G_BLOCKMASK;\n\t\t\t\t//int k = cell_id_in_block & config::G_BLOCKMASK;\n\n\t\t\t\t//Fetch current velocity\n\t\t\t\tvel[0] = grid_block.val_1d(_1, cell_id_in_block);\n\t\t\t\tvel[1] = grid_block.val_1d(_2, cell_id_in_block);\n\t\t\t\tvel[2] = grid_block.val_1d(_3, cell_id_in_block);\n\n\t\t\t\t//Update velocity. Set to 0 if outside of bounds\n\t\t\t\tvel[0] = is_in_bound & 4 ? 0.0f : vel[0] * mass_inv;\n\t\t\t\tvel[1] = is_in_bound & 2 ? 0.0f : vel[1] * mass_inv;\n\t\t\t\tvel[1] += config::G_GRAVITY * dt.count();\n\t\t\t\tvel[2] = is_in_bound & 1 ? 0.0f : vel[2] * mass_inv;\n\t\t\t\t// if (is_in_bound) ///< sticky\n\t\t\t\t// vel.set(0.f);\n\n\t\t\t\t//Write back velocity\n\t\t\t\tgrid_block.val_1d(_1, cell_id_in_block) = vel[0];\n\t\t\t\tgrid_block.val_1d(_2, cell_id_in_block) = vel[1];\n\t\t\t\tgrid_block.val_1d(_3, cell_id_in_block) = vel[2];\n\n\t\t\t\t//Calculate squared velocity\n\t\t\t\tvel_sqr += vel[0] * vel[0];\n\t\t\t\tvel_sqr += vel[1] * vel[1];\n\t\t\t\tvel_sqr += vel[2] * vel[2];\n\t\t\t}\n\n\t\t\t//If we have nan values, signalize failure by setting max_vel to inf\n\t\t\tif(isnan(vel_sqr)) {\n\t\t\t\tvel_sqr = std::numeric_limits::infinity();\n\t\t\t}\n\n\t\t\t// unsigned activeMask = __ballot_sync(0xffffffff, mv[0] != 0.0f);\n\n\t\t\t//Calculate max velocity in warp\n\t\t\tfor(int iter = 1; iter % config::CUDA_WARP_SIZE; iter <<= 1) {\n\t\t\t\tfloat tmp = __shfl_down_sync(ACTIVE_MASK, vel_sqr, iter, config::CUDA_WARP_SIZE);\n\t\t\t\tif((threadIdx.x % config::CUDA_WARP_SIZE) + iter < config::CUDA_WARP_SIZE) {\n\t\t\t\t\tvel_sqr = tmp > vel_sqr ? tmp : vel_sqr;\n\t\t\t\t}\n\t\t\t}\n\t\t\t//TODO: Ensure threadIdx.x / config::CUDA_WARP_SIZE is smaller than NUM_WARPS\n\t\t\tif(vel_sqr > sh_maxvels[threadIdx.x / config::CUDA_WARP_SIZE] && (threadIdx.x % config::CUDA_WARP_SIZE) == 0) {\n\t\t\t\tsh_maxvels[threadIdx.x / config::CUDA_WARP_SIZE] = vel_sqr;\n\t\t\t}\n\t\t}\n\t}\n\t__syncthreads();\n\n\t//Calculate global max velocity\n\t/// various assumptions\n\tfor(int interval = NUM_WARPS >> 1; interval > 0; interval >>= 1) {\n\t\tif(threadIdx.x < interval) {\n\t\t\tif(sh_maxvels[static_cast(threadIdx.x) + interval] > sh_maxvels[threadIdx.x]) {\n\t\t\t\tsh_maxvels[threadIdx.x] = sh_maxvels[static_cast(threadIdx.x) + interval];\n\t\t\t}\n\t\t}\n\t\t__syncthreads();\n\t}\n\tif(threadIdx.x == 0) {\n\t\tatomic_max(max_vel, sh_maxvels[0]);\n\t}\n}\n\n//Need this, cause we cannot partially instantiate function templates in current c++ version\nstruct FetchParticleBufferDataIntermediate {\n\tvec3 pos;\n\tfloat J;\n};\n\ntemplate\n__forceinline__ __device__ void fetch_particle_buffer_data(const ParticleBuffer particle_buffer, int advection_source_blockno, int source_pidib, FetchParticleBufferDataIntermediate& data);\n\ntemplate<>\n__forceinline__ __device__ void fetch_particle_buffer_data(const ParticleBuffer particle_buffer, int advection_source_blockno, int source_pidib, FetchParticleBufferDataIntermediate& data) {\n\tauto source_particle_bin = particle_buffer.ch(_0, advection_source_blockno);\n\tdata.pos[0]\t\t\t\t = source_particle_bin.val(_0, source_pidib % config::G_BIN_CAPACITY);\n\tdata.pos[1]\t\t\t\t = source_particle_bin.val(_1, source_pidib % config::G_BIN_CAPACITY);\n\tdata.pos[2]\t\t\t\t = source_particle_bin.val(_2, source_pidib % config::G_BIN_CAPACITY);\n\tdata.J\t\t\t\t\t = source_particle_bin.val(_3, source_pidib % config::G_BIN_CAPACITY);\n}\n\ntemplate<>\n__forceinline__ __device__ void fetch_particle_buffer_data(const ParticleBuffer particle_buffer, int advection_source_blockno, int source_pidib, FetchParticleBufferDataIntermediate& data) {\n\tauto source_particle_bin = particle_buffer.ch(_0, advection_source_blockno);\n\tdata.pos[0]\t\t\t\t = source_particle_bin.val(_0, source_pidib % config::G_BIN_CAPACITY);\n\tdata.pos[1]\t\t\t\t = source_particle_bin.val(_1, source_pidib % config::G_BIN_CAPACITY);\n\tdata.pos[2]\t\t\t\t = source_particle_bin.val(_2, source_pidib % config::G_BIN_CAPACITY);\n}\n\ntemplate<>\n__forceinline__ __device__ void fetch_particle_buffer_data(const ParticleBuffer particle_buffer, int advection_source_blockno, int source_pidib, FetchParticleBufferDataIntermediate& data) {\n\tauto source_particle_bin = particle_buffer.ch(_0, advection_source_blockno);\n\tdata.pos[0]\t\t\t\t = source_particle_bin.val(_0, source_pidib % config::G_BIN_CAPACITY);\n\tdata.pos[1]\t\t\t\t = source_particle_bin.val(_1, source_pidib % config::G_BIN_CAPACITY);\n\tdata.pos[2]\t\t\t\t = source_particle_bin.val(_2, source_pidib % config::G_BIN_CAPACITY);\n}\n\ntemplate<>\n__forceinline__ __device__ void fetch_particle_buffer_data(const ParticleBuffer particle_buffer, int advection_source_blockno, int source_pidib, FetchParticleBufferDataIntermediate& data) {\n\tauto source_particle_bin = particle_buffer.ch(_0, advection_source_blockno);\n\tdata.pos[0]\t\t\t\t = source_particle_bin.val(_0, source_pidib % config::G_BIN_CAPACITY);\n\tdata.pos[1]\t\t\t\t = source_particle_bin.val(_1, source_pidib % config::G_BIN_CAPACITY);\n\tdata.pos[2]\t\t\t\t = source_particle_bin.val(_2, source_pidib % config::G_BIN_CAPACITY);\n}\n\n//Need this, cause we cannot partially instantiate function templates in current c++ version\nstruct CalculateContributionAndStoreParticleDataIntermediate {\n\tvec3 pos;\n\tfloat J;\n};\n\ntemplate\n__forceinline__ __device__ void calculate_contribution_and_store_particle_data(const ParticleBuffer particle_buffer, const ParticleBuffer next_particle_buffer, int advection_source_blockno, int source_pidib, int src_blockno, int particle_id_in_block, Duration dt, const std::array& A, std::array& contrib, CalculateContributionAndStoreParticleDataIntermediate& data);\n\ntemplate<>\n__forceinline__ __device__ void calculate_contribution_and_store_particle_data(const ParticleBuffer particle_buffer, const ParticleBuffer next_particle_buffer, int advection_source_blockno, int source_pidib, int src_blockno, int particle_id_in_block, Duration dt, const std::array& A, std::array& contrib, CalculateContributionAndStoreParticleDataIntermediate& data) {\n\t(void) advection_source_blockno;\n\t(void) source_pidib;\n\n\t//Update determinante of deformation gradiant\n\t//Divergence of velocity multiplied with time and transfered to global space\n\tdata.J += (A[0] + A[4] + A[8]) * dt.count() * config::G_D_INV * data.J;\n\n\t//Too low is bad. clamp to 0.1\n\t//TODO: Maybe make this 0.1 a parameter\n\tif(data.J < 0.1) {\n\t\tdata.J = 0.1;\n\t}\n\n\t//TODO: What is calculated here?\n\t{\n\t\tfloat voln\t = data.J * particle_buffer.volume;\n\t\tfloat pressure = particle_buffer.bulk * (powf(data.J, -particle_buffer.gamma) - 1.f);\n\t\t//? - stress; stress = pressure * identity;\n\t\t{\n\t\t\tcontrib[0] = ((A[0] + A[0]) * config::G_D_INV * particle_buffer.viscosity - pressure) * voln;\n\t\t\tcontrib[1] = (A[1] + A[3]) * config::G_D_INV * particle_buffer.viscosity * voln;\n\t\t\tcontrib[2] = (A[2] + A[6]) * config::G_D_INV * particle_buffer.viscosity * voln;\n\n\t\t\tcontrib[3] = (A[3] + A[1]) * config::G_D_INV * particle_buffer.viscosity * voln;\n\t\t\tcontrib[4] = ((A[4] + A[4]) * config::G_D_INV * particle_buffer.viscosity - pressure) * voln;\n\t\t\tcontrib[5] = (A[5] + A[7]) * config::G_D_INV * particle_buffer.viscosity * voln;\n\n\t\t\tcontrib[6] = (A[6] + A[2]) * config::G_D_INV * particle_buffer.viscosity * voln;\n\t\t\tcontrib[7] = (A[7] + A[5]) * config::G_D_INV * particle_buffer.viscosity * voln;\n\t\t\tcontrib[8] = ((A[8] + A[8]) * config::G_D_INV * particle_buffer.viscosity - pressure) * voln;\n\t\t}\n\t}\n\n\t//Write back particle data\n\t{\n\t\tauto particle_bin\t\t\t\t\t\t\t\t\t\t\t\t\t= next_particle_buffer.ch(_0, next_particle_buffer.bin_offsets[src_blockno] + particle_id_in_block / config::G_BIN_CAPACITY);\n\t\tparticle_bin.val(_0, particle_id_in_block % config::G_BIN_CAPACITY) = data.pos[0];\n\t\tparticle_bin.val(_1, particle_id_in_block % config::G_BIN_CAPACITY) = data.pos[1];\n\t\tparticle_bin.val(_2, particle_id_in_block % config::G_BIN_CAPACITY) = data.pos[2];\n\t\tparticle_bin.val(_3, particle_id_in_block % config::G_BIN_CAPACITY) = data.J;\n\t}\n}\n\ntemplate<>\n__forceinline__ __device__ void calculate_contribution_and_store_particle_data(const ParticleBuffer particle_buffer, const ParticleBuffer next_particle_buffer, int advection_source_blockno, int source_pidib, int src_blockno, int particle_id_in_block, Duration dt, const std::array& A, std::array& contrib, CalculateContributionAndStoreParticleDataIntermediate& data) {\n\tvec3x3 dws;\n//((d & 0x3) != 0 ? 0.f : 1.f) is identity matrix\n#pragma unroll 9\n\tfor(int d = 0; d < 9; ++d) {\n\t\tdws.val(d) = A[d] * dt.count() * config::G_D_INV + ((d & 0x3) != 0 ? 0.f : 1.f);\n\t}\n\n\t{\n\t\tvec9 F;\n\t\tauto source_particle_bin = particle_buffer.ch(_0, advection_source_blockno);\n\t\tcontrib[0]\t\t\t\t = source_particle_bin.val(_3, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[1]\t\t\t\t = source_particle_bin.val(_4, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[2]\t\t\t\t = source_particle_bin.val(_5, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[3]\t\t\t\t = source_particle_bin.val(_6, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[4]\t\t\t\t = source_particle_bin.val(_7, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[5]\t\t\t\t = source_particle_bin.val(_8, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[6]\t\t\t\t = source_particle_bin.val(_9, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[7]\t\t\t\t = source_particle_bin.val(_10, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[8]\t\t\t\t = source_particle_bin.val(_11, source_pidib % config::G_BIN_CAPACITY);\n\t\tmatrix_matrix_multiplication_3d(dws.data_arr(), contrib, F.data_arr());\n\t\t{\n\t\t\tauto particle_bin\t\t\t\t\t\t\t\t\t\t\t\t\t = next_particle_buffer.ch(_0, next_particle_buffer.bin_offsets[src_blockno] + particle_id_in_block / config::G_BIN_CAPACITY);\n\t\t\tparticle_bin.val(_0, particle_id_in_block % config::G_BIN_CAPACITY)\t = data.pos[0];\n\t\t\tparticle_bin.val(_1, particle_id_in_block % config::G_BIN_CAPACITY)\t = data.pos[1];\n\t\t\tparticle_bin.val(_2, particle_id_in_block % config::G_BIN_CAPACITY)\t = data.pos[2];\n\t\t\tparticle_bin.val(_3, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[0];\n\t\t\tparticle_bin.val(_4, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[1];\n\t\t\tparticle_bin.val(_5, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[2];\n\t\t\tparticle_bin.val(_6, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[3];\n\t\t\tparticle_bin.val(_7, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[4];\n\t\t\tparticle_bin.val(_8, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[5];\n\t\t\tparticle_bin.val(_9, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[6];\n\t\t\tparticle_bin.val(_10, particle_id_in_block % config::G_BIN_CAPACITY) = F[7];\n\t\t\tparticle_bin.val(_11, particle_id_in_block % config::G_BIN_CAPACITY) = F[8];\n\t\t}\n\t\tComputeStressIntermediate compute_stress_tmp = {};\n\t\tcompute_stress(particle_buffer.volume, particle_buffer.mu, particle_buffer.lambda, F.data_arr(), contrib, compute_stress_tmp);\n\t}\n}\n\ntemplate<>\n__forceinline__ __device__ void calculate_contribution_and_store_particle_data(const ParticleBuffer particle_buffer, const ParticleBuffer next_particle_buffer, int advection_source_blockno, int source_pidib, int src_blockno, int particle_id_in_block, Duration dt, const std::array& A, std::array& contrib, CalculateContributionAndStoreParticleDataIntermediate& data) {\n\tvec3x3 dws;\n//((d & 0x3) != 0 ? 0.f : 1.f) is identity matrix\n#pragma unroll 9\n\tfor(int d = 0; d < 9; ++d) {\n\t\tdws.val(d) = A[d] * dt.count() * config::G_D_INV + ((d & 0x3) != 0 ? 0.f : 1.f);\n\t}\n\n\t{\n\t\tvec9 F;\n\t\tfloat log_jp;\n\t\tauto source_particle_bin = particle_buffer.ch(_0, advection_source_blockno);\n\t\tcontrib[0]\t\t\t\t = source_particle_bin.val(_3, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[1]\t\t\t\t = source_particle_bin.val(_4, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[2]\t\t\t\t = source_particle_bin.val(_5, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[3]\t\t\t\t = source_particle_bin.val(_6, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[4]\t\t\t\t = source_particle_bin.val(_7, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[5]\t\t\t\t = source_particle_bin.val(_8, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[6]\t\t\t\t = source_particle_bin.val(_9, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[7]\t\t\t\t = source_particle_bin.val(_10, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[8]\t\t\t\t = source_particle_bin.val(_11, source_pidib % config::G_BIN_CAPACITY);\n\t\tlog_jp\t\t\t\t\t = source_particle_bin.val(_12, source_pidib % config::G_BIN_CAPACITY);\n\n\t\tmatrix_matrix_multiplication_3d(dws.data_arr(), contrib, F.data_arr());\n\t\tComputeStressIntermediate compute_stress_tmp = {};\n\t\tcompute_stress_tmp.cohesion\t\t\t\t\t = particle_buffer.cohesion;\n\t\tcompute_stress_tmp.beta\t\t\t\t\t\t = particle_buffer.beta;\n\t\tcompute_stress_tmp.yield_surface\t\t\t = particle_buffer.yield_surface;\n\t\tcompute_stress_tmp.volume_correction\t\t = particle_buffer.volume_correction;\n\t\tcompute_stress_tmp.log_jp\t\t\t\t\t = log_jp;\n\t\tcompute_stress(particle_buffer.volume, particle_buffer.mu, particle_buffer.lambda, F.data_arr(), contrib, compute_stress_tmp);\n\t\tlog_jp = compute_stress_tmp.log_jp;\n\t\t{\n\t\t\tauto particle_bin\t\t\t\t\t\t\t\t\t\t\t\t\t = next_particle_buffer.ch(_0, next_particle_buffer.bin_offsets[src_blockno] + particle_id_in_block / config::G_BIN_CAPACITY);\n\t\t\tparticle_bin.val(_0, particle_id_in_block % config::G_BIN_CAPACITY)\t = data.pos[0];\n\t\t\tparticle_bin.val(_1, particle_id_in_block % config::G_BIN_CAPACITY)\t = data.pos[1];\n\t\t\tparticle_bin.val(_2, particle_id_in_block % config::G_BIN_CAPACITY)\t = data.pos[2];\n\t\t\tparticle_bin.val(_3, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[0];\n\t\t\tparticle_bin.val(_4, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[1];\n\t\t\tparticle_bin.val(_5, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[2];\n\t\t\tparticle_bin.val(_6, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[3];\n\t\t\tparticle_bin.val(_7, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[4];\n\t\t\tparticle_bin.val(_8, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[5];\n\t\t\tparticle_bin.val(_9, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[6];\n\t\t\tparticle_bin.val(_10, particle_id_in_block % config::G_BIN_CAPACITY) = F[7];\n\t\t\tparticle_bin.val(_11, particle_id_in_block % config::G_BIN_CAPACITY) = F[8];\n\t\t\tparticle_bin.val(_12, particle_id_in_block % config::G_BIN_CAPACITY) = log_jp;\n\t\t}\n\t}\n}\n\ntemplate<>\n__forceinline__ __device__ void calculate_contribution_and_store_particle_data(const ParticleBuffer particle_buffer, const ParticleBuffer next_particle_buffer, int advection_source_blockno, int source_pidib, int src_blockno, int particle_id_in_block, Duration dt, const std::array& A, std::array& contrib, CalculateContributionAndStoreParticleDataIntermediate& data) {\n\tvec3x3 dws;\n//((d & 0x3) != 0 ? 0.f : 1.f) is identity matrix\n#pragma unroll 9\n\tfor(int d = 0; d < 9; ++d) {\n\t\tdws.val(d) = A[d] * dt.count() * config::G_D_INV + ((d & 0x3) != 0 ? 0.f : 1.f);\n\t}\n\n\t{\n\t\tvec9 F;\n\t\tfloat log_jp;\n\t\tauto source_particle_bin = particle_buffer.ch(_0, advection_source_blockno);\n\t\tcontrib[0]\t\t\t\t = source_particle_bin.val(_3, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[1]\t\t\t\t = source_particle_bin.val(_4, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[2]\t\t\t\t = source_particle_bin.val(_5, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[3]\t\t\t\t = source_particle_bin.val(_6, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[4]\t\t\t\t = source_particle_bin.val(_7, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[5]\t\t\t\t = source_particle_bin.val(_8, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[6]\t\t\t\t = source_particle_bin.val(_9, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[7]\t\t\t\t = source_particle_bin.val(_10, source_pidib % config::G_BIN_CAPACITY);\n\t\tcontrib[8]\t\t\t\t = source_particle_bin.val(_11, source_pidib % config::G_BIN_CAPACITY);\n\t\tlog_jp\t\t\t\t\t = source_particle_bin.val(_12, source_pidib % config::G_BIN_CAPACITY);\n\n\t\tmatrix_matrix_multiplication_3d(dws.data_arr(), contrib, F.data_arr());\n\t\tComputeStressIntermediate compute_stress_tmp = {};\n\t\tcompute_stress_tmp.bm\t\t\t\t\t\t = particle_buffer.bm;\n\t\tcompute_stress_tmp.xi\t\t\t\t\t\t = particle_buffer.xi;\n\t\tcompute_stress_tmp.beta\t\t\t\t\t\t = particle_buffer.beta;\n\t\tcompute_stress_tmp.msqr\t\t\t\t\t\t = particle_buffer.msqr;\n\t\tcompute_stress_tmp.hardening_on\t\t\t\t = particle_buffer.hardening_on;\n\t\tcompute_stress_tmp.log_jp\t\t\t\t\t = log_jp;\n\t\tcompute_stress(particle_buffer.volume, particle_buffer.mu, particle_buffer.lambda, F.data_arr(), contrib, compute_stress_tmp);\n\t\tlog_jp = compute_stress_tmp.log_jp;\n\t\t{\n\t\t\tauto particle_bin\t\t\t\t\t\t\t\t\t\t\t\t\t = next_particle_buffer.ch(_0, next_particle_buffer.bin_offsets[src_blockno] + particle_id_in_block / config::G_BIN_CAPACITY);\n\t\t\tparticle_bin.val(_0, particle_id_in_block % config::G_BIN_CAPACITY)\t = data.pos[0];\n\t\t\tparticle_bin.val(_1, particle_id_in_block % config::G_BIN_CAPACITY)\t = data.pos[1];\n\t\t\tparticle_bin.val(_2, particle_id_in_block % config::G_BIN_CAPACITY)\t = data.pos[2];\n\t\t\tparticle_bin.val(_3, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[0];\n\t\t\tparticle_bin.val(_4, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[1];\n\t\t\tparticle_bin.val(_5, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[2];\n\t\t\tparticle_bin.val(_6, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[3];\n\t\t\tparticle_bin.val(_7, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[4];\n\t\t\tparticle_bin.val(_8, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[5];\n\t\t\tparticle_bin.val(_9, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[6];\n\t\t\tparticle_bin.val(_10, particle_id_in_block % config::G_BIN_CAPACITY) = F[7];\n\t\t\tparticle_bin.val(_11, particle_id_in_block % config::G_BIN_CAPACITY) = F[8];\n\t\t\tparticle_bin.val(_12, particle_id_in_block % config::G_BIN_CAPACITY) = log_jp;\n\t\t}\n\t}\n}\n\ntemplate\n__global__ void g2p2g(Duration dt, Duration new_dt, const ParticleBuffer particle_buffer, ParticleBuffer next_particle_buffer, const Partition prev_partition, Partition partition, const Grid grid, Grid next_grid) {\n\tstatic constexpr uint64_t NUM_VI_PER_BLOCK = static_cast(config::G_BLOCKVOLUME) * 3;\n\tstatic constexpr uint64_t NUM_VI_IN_ARENA = NUM_VI_PER_BLOCK << 3;\n\n\tstatic constexpr uint64_t NUM_M_VI_PER_BLOCK = static_cast(config::G_BLOCKVOLUME) * 4;\n\tstatic constexpr uint64_t NUM_M_VI_IN_ARENA\t = NUM_M_VI_PER_BLOCK << 3;\n\n\tstatic constexpr unsigned ARENAMASK = (config::G_BLOCKSIZE << 1) - 1;\n\tstatic constexpr unsigned ARENABITS = config::G_BLOCKBITS + 1;\n\n\tusing ViArena\t = std::array, config::G_BLOCKSIZE << 1>, config::G_BLOCKSIZE << 1>, 3>*;\n\tusing ViArenaRef = std::array, config::G_BLOCKSIZE << 1>, config::G_BLOCKSIZE << 1>, 3>&;\n\tusing MViArena\t = std::array, config::G_BLOCKSIZE << 1>, config::G_BLOCKSIZE << 1>, 4>*;\n\tusing MViArenaRef = std::array, config::G_BLOCKSIZE << 1>, config::G_BLOCKSIZE << 1>, 4>&;\n\n\tstatic constexpr size_t shared_memory_size = static_cast((3 + 4) * (config::G_BLOCKSIZE << 1) * (config::G_BLOCKSIZE << 1) * (config::G_BLOCKSIZE << 1)) * sizeof(float);\n\t__shared__ char shmem[shared_memory_size];//NOLINT(modernize-avoid-c-arrays, readability-redundant-declaration) Cannot declare runtime size shared memory as std::array; extern has different meaning here\n\n\tViArenaRef __restrict__ g2pbuffer = *static_cast(static_cast(static_cast(shmem)));\n\tMViArenaRef __restrict__ p2gbuffer = *static_cast(static_cast(static_cast(shmem) + NUM_VI_IN_ARENA * sizeof(float)));\n\n\t//Layout of buffers: 1 dimension is channel. other dimensions range [0, 3] contains current block, range [4, 7] contains next block\n\t//The first cell of the next block is handled by the current block only (but may receive values of particles traveling out of next block in negative direction)\n\n\tconst int src_blockno\t\t = static_cast(blockIdx.x);\n\tconst auto blockid\t\t\t = partition.active_keys[blockIdx.x];\n\tconst int particle_bucket_size = next_particle_buffer.particle_bucket_sizes[src_blockno];\n\n\t//If we have no particles in the bucket return\n\tif(particle_bucket_size == 0) {\n\t\treturn;\n\t}\n\n\t//Load data from grid to shared memory\n\tfor(int base = static_cast(threadIdx.x); base < NUM_VI_IN_ARENA; base += static_cast(blockDim.x)) {\n\t\tconst char local_block_id = static_cast(base / NUM_VI_PER_BLOCK);\n\t\tconst auto blockno\t\t = partition.query(ivec3 {blockid[0] + ((local_block_id & 4) != 0 ? 1 : 0), blockid[1] + ((local_block_id & 2) != 0 ? 1 : 0), blockid[2] + ((local_block_id & 1) != 0 ? 1 : 0)});\n\t\tconst auto grid_block\t = grid.ch(_0, blockno);\n\t\tint channelid\t\t\t = static_cast(base % NUM_VI_PER_BLOCK);\n\t\tconst char c\t\t\t = static_cast(channelid & 0x3f);\n\n\t\tconst char cz = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tconst char cy = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tconst char cx = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tfloat val;\n\t\tif(channelid == 0) {\n\t\t\tval = grid_block.val_1d(_1, c);\n\t\t} else if(channelid == 1) {\n\t\t\tval = grid_block.val_1d(_2, c);\n\t\t} else {\n\t\t\tval = grid_block.val_1d(_3, c);\n\t\t}\n\n\t\tg2pbuffer[channelid][static_cast(static_cast(cx) + (local_block_id & 4 ? config::G_BLOCKSIZE : 0))][static_cast(static_cast(cy) + (local_block_id & 2 ? config::G_BLOCKSIZE : 0))][static_cast(static_cast(cz) + (local_block_id & 1 ? config::G_BLOCKSIZE : 0))] = val;\n\t}\n\t__syncthreads();\n\n\t//Clear return buffer\n\tfor(int base = static_cast(threadIdx.x); base < NUM_M_VI_IN_ARENA; base += static_cast(blockDim.x)) {\n\t\tint loc\t\t = base;\n\t\tconst char z = static_cast(loc & ARENAMASK);\n\t\tloc >>= ARENABITS;\n\n\t\tconst char y = static_cast(loc & ARENAMASK);\n\t\tloc >>= ARENABITS;\n\n\t\tconst char x = static_cast(loc & ARENAMASK);\n\n\t\tp2gbuffer[loc >> ARENABITS][x][y][z] = 0.0f;\n\t}\n\t__syncthreads();\n\n\t//Perform update\n\tfor(int particle_id_in_block = static_cast(threadIdx.x); particle_id_in_block < particle_bucket_size; particle_id_in_block += static_cast(blockDim.x)) {\n\t\t//Fetch index of the advection source\n\t\tint advection_source_blockno;\n\t\tint source_pidib;\n\t\t{\n\t\t\t//Fetch advection (direction at high bits, particle in in cell at low bits)\n\t\t\tconst int advect = next_particle_buffer.blockbuckets[src_blockno * config::G_PARTICLE_NUM_PER_BLOCK + particle_id_in_block];\n\n\t\t\t//Retrieve the direction (first stripping the particle id by division)\n\t\t\tivec3 offset;\n\t\t\tdir_components(advect / config::G_PARTICLE_NUM_PER_BLOCK, offset.data_arr());\n\n\t\t\t//Retrieve the particle id by AND for lower bits\n\t\t\tsource_pidib = advect & (config::G_PARTICLE_NUM_PER_BLOCK - 1);\n\n\t\t\t//Get global index by adding blockid and offset\n\t\t\tconst ivec3 global_advection_index = blockid + offset;\n\n\t\t\t//Get block_no from partition\n\t\t\tconst int advection_source_blockno_from_partition = prev_partition.query(global_advection_index);\n\n\t\t\t//Get block number in particle bins\n\t\t\tadvection_source_blockno = particle_buffer.bin_offsets[advection_source_blockno_from_partition] + source_pidib / config::G_BIN_CAPACITY;\n\t\t}\n\n\t\t//Fetch position and determinant of deformation gradient\n\t\tFetchParticleBufferDataIntermediate fetch_particle_buffer_tmp = {};\n\t\tfetch_particle_buffer_data(particle_buffer, advection_source_blockno, source_pidib, fetch_particle_buffer_tmp);\n\t\tvec3 pos = fetch_particle_buffer_tmp.pos;\n\t\tfloat J\t = fetch_particle_buffer_tmp.J;\n\n\t\t//Get position of grid cell\n\t\tivec3 global_base_index = get_block_id(pos.data_arr()) - 1;\n\n\t\t//Get position relative to grid cell\n\t\tvec3 local_pos = pos - global_base_index * config::G_DX;\n\n\t\t//Save global_base_index\n\t\tivec3 base_index = global_base_index;\n\n\t\t//Calculate weights and mask global index\n\t\tvec3x3 dws;\n#pragma unroll 3\n\t\tfor(int dd = 0; dd < 3; ++dd) {\n\t\t\tconst vec3 weight = bspline_weight(local_pos[dd]);\n\t\t\tdws(dd, 0)\t\t = weight[0];\n\t\t\tdws(dd, 1)\t\t = weight[1];\n\t\t\tdws(dd, 2)\t\t = weight[2];\n\n\t\t\t//Calculate (modulo (config::G_BLOCKMASK + 1)) + 1 of index (== (..., -4, -3, -2, -1, 0, 1, 2, 3, 4, ...) -> (..., 4, 1, 2, 3, 4, 1, 2, 3, 4, ...))\n\t\t\tglobal_base_index[dd] = ((base_index[dd] - 1) & config::G_BLOCKMASK) + 1;\n\t\t}\n\n\t\t//Calculate particle velocity and APIC affine matrix\n\t\t//v_p = sum(i, weight_i_p * v_i)\n\t\t//A = sum(i, weight_i_p * v_i * (x_i - x_p))\n\t\tvec3 vel;\n\t\tvel.set(0.f);\n\t\tvec9 A;//affine state\n\t\tA.set(0.f);\n#pragma unroll 3\n\t\tfor(char i = 0; i < 3; i++) {\n#pragma unroll 3\n\t\t\tfor(char j = 0; j < 3; j++) {\n#pragma unroll 3\n\t\t\t\tfor(char k = 0; k < 3; k++) {\n\t\t\t\t\t//(x_i - x_p)\n\t\t\t\t\tconst vec3 xixp = vec3 {static_cast(i), static_cast(j), static_cast(k)} * config::G_DX - local_pos;\n\n\t\t\t\t\t//Weight\n\t\t\t\t\tconst float W = dws(0, i) * dws(1, j) * dws(2, k);\n\n\t\t\t\t\t//Velocity of grid cell\n\t\t\t\t\tconst vec3 vi {g2pbuffer[0][static_cast(static_cast(global_base_index[0]) + i)][static_cast(static_cast(global_base_index[1]) + j)][static_cast(static_cast(global_base_index[2]) + k)], g2pbuffer[1][static_cast(static_cast(global_base_index[0]) + i)][static_cast(static_cast(global_base_index[1]) + j)][static_cast(static_cast(global_base_index[2]) + k)], g2pbuffer[2][static_cast(static_cast(global_base_index[0]) + i)][static_cast(static_cast(global_base_index[1]) + j)][static_cast(static_cast(global_base_index[2]) + k)]};\n\n\t\t\t\t\t//Calculate velocity\n\t\t\t\t\tvel += W * vi;\n\n\t\t\t\t\t//Calculate APIC affine matrix\n\t\t\t\t\tA[0] += W * vi[0] * xixp[0];\n\t\t\t\t\tA[1] += W * vi[1] * xixp[0];\n\t\t\t\t\tA[2] += W * vi[2] * xixp[0];\n\t\t\t\t\tA[3] += W * vi[0] * xixp[1];\n\t\t\t\t\tA[4] += W * vi[1] * xixp[1];\n\t\t\t\t\tA[5] += W * vi[2] * xixp[1];\n\t\t\t\t\tA[6] += W * vi[0] * xixp[2];\n\t\t\t\t\tA[7] += W * vi[1] * xixp[2];\n\t\t\t\t\tA[8] += W * vi[2] * xixp[2];\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\n\t\t//Update particle position\n\t\tpos += vel * dt.count();\n\n\t\tCalculateContributionAndStoreParticleDataIntermediate store_particle_buffer_tmp = {};\n\t\tstore_particle_buffer_tmp.pos\t\t\t\t\t\t\t\t\t\t\t\t\t= pos;\n\t\tstore_particle_buffer_tmp.J\t\t\t\t\t\t\t\t\t\t\t\t\t\t= J;\n\n\t\tvec9 contrib;\n\t\tcalculate_contribution_and_store_particle_data(particle_buffer, next_particle_buffer, advection_source_blockno, source_pidib, src_blockno, particle_id_in_block, dt, A.data_arr(), contrib.data_arr(), store_particle_buffer_tmp);\n\n\t\t//Update momentum?\n\t\t//Multiply A with mass to complete it. Then subtract current momentum?\n\t\t//C = A * D^-1\n\t\tcontrib = (A * particle_buffer.mass - contrib * new_dt.count()) * config::G_D_INV;\n\n\t\t//Calculate grid index after movement\n\t\tivec3 new_global_base_index = get_block_id(pos.data_arr()) - 1;\n\n\t\t//Update local position\n\t\tlocal_pos = pos - new_global_base_index * config::G_DX;\n\n\t\t//Store index and movement direction\n\t\t{\n\t\t\t//Calculate direction offset\n\t\t\tconst int dirtag = dir_offset(((base_index - 1) / static_cast(config::G_BLOCKSIZE) - (new_global_base_index - 1) / static_cast(config::G_BLOCKSIZE)).data_arr());\n\n\t\t\t//Store particle in new block\n\t\t\tnext_particle_buffer.add_advection(partition, new_global_base_index - 1, dirtag, particle_id_in_block);\n\t\t\t// partition.add_advection(new_global_base_index - 1, dirtag, particle_id_in_block);\n\t\t}\n\n\t\t//Calculate weights and mask global index\n#pragma unroll 3\n\t\tfor(char dd = 0; dd < 3; ++dd) {\n\t\t\tconst vec3 weight = bspline_weight(local_pos[dd]);\n\t\t\tdws(dd, 0)\t\t = weight[0];\n\t\t\tdws(dd, 1)\t\t = weight[1];\n\t\t\tdws(dd, 2)\t\t = weight[2];\n\n\t\t\t//Calculate (modulo (config::G_BLOCKMASK + 1)) + 1 of index (== (..., -4, -3, -2, -1, 0, 1, 2, 3, 4, ...) -> (..., 4, 1, 2, 3, 4, 1, 2, 3, 4, ...)) and add offset (may not be out of range max [-4, 4] min [-1, 1])\n\t\t\tnew_global_base_index[dd] = (((base_index[dd] - 1) & config::G_BLOCKMASK) + 1) + (new_global_base_index[dd] - base_index[dd]);\n\t\t}\n\n\t\t//Dim of p2gbuffer is (4, 8, 8, 8). So if values are too big, discard whole particle\n\t\tif(new_global_base_index[0] < 0 || new_global_base_index[1] < 0 || new_global_base_index[2] < 0 || new_global_base_index[0] + 2 >= 8 || new_global_base_index[1] + 2 >= 8 || new_global_base_index[2] + 2 >= 8) {\n\t\t\t//NOLINTNEXTLINE(cppcoreguidelines-pro-type-vararg) Cuda has no other way to print; Numbers are array indices to be printed\n\t\t\tprintf(\"new_global_base_index out of range: %d %d %d\\n\", new_global_base_index[0], new_global_base_index[1], new_global_base_index[2]);\n\t\t\treturn;\n\t\t}\n\n\t\t//Calculate new gird momentum and mass\n\t\t//m_i * v_i = sum(p, w_i_p * m_p * vel_p + ?)\n#pragma unroll 3\n\t\tfor(char i = 0; i < 3; i++) {\n#pragma unroll 3\n\t\t\tfor(char j = 0; j < 3; j++) {\n#pragma unroll 3\n\t\t\t\tfor(char k = 0; k < 3; k++) {\n\t\t\t\t\tpos\t\t\t = vec3 {static_cast(i), static_cast(j), static_cast(k)} * config::G_DX - local_pos;\n\t\t\t\t\tconst float W = dws(0, i) * dws(1, j) * dws(2, k);\n\t\t\t\t\tconst auto wm = particle_buffer.mass * W;\n\n\t\t\t\t\tatomicAdd(&p2gbuffer[0][static_cast(static_cast(new_global_base_index[0]) + i)][static_cast(static_cast(new_global_base_index[1]) + j)][static_cast(static_cast(new_global_base_index[2]) + k)], wm);\n\t\t\t\t\tatomicAdd(&p2gbuffer[1][static_cast(static_cast(new_global_base_index[0]) + i)][static_cast(static_cast(new_global_base_index[1]) + j)][static_cast(static_cast(new_global_base_index[2]) + k)], wm * vel[0] + (contrib[0] * pos[0] + contrib[3] * pos[1] + contrib[6] * pos[2]) * W);\n\t\t\t\t\tatomicAdd(&p2gbuffer[2][static_cast(static_cast(new_global_base_index[0]) + i)][static_cast(static_cast(new_global_base_index[1]) + j)][static_cast(static_cast(new_global_base_index[2]) + k)], wm * vel[1] + (contrib[1] * pos[0] + contrib[4] * pos[1] + contrib[7] * pos[2]) * W);\n\t\t\t\t\tatomicAdd(&p2gbuffer[3][static_cast(static_cast(new_global_base_index[0]) + i)][static_cast(static_cast(new_global_base_index[1]) + j)][static_cast(static_cast(new_global_base_index[2]) + k)], wm * vel[2] + (contrib[2] * pos[0] + contrib[5] * pos[1] + contrib[8] * pos[2]) * W);\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\t__syncthreads();\n\n\t//Store data from shared memory to grid\n\tfor(int base = static_cast(threadIdx.x); base < NUM_M_VI_IN_ARENA; base += static_cast(blockDim.x)) {\n\t\tconst char local_block_id = static_cast(base / NUM_M_VI_PER_BLOCK);\n\t\tconst auto blockno\t\t = partition.query(ivec3 {blockid[0] + ((local_block_id & 4) != 0 ? 1 : 0), blockid[1] + ((local_block_id & 2) != 0 ? 1 : 0), blockid[2] + ((local_block_id & 1) != 0 ? 1 : 0)});\n\t\t// auto grid_block = next_grid.template ch<0>(blockno);\n\t\tint channelid = static_cast(base & (NUM_M_VI_PER_BLOCK - 1));\n\t\tconst char c = static_cast(channelid % config::G_BLOCKVOLUME);\n\n\t\tconst char cz = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tconst char cy = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tconst char cx = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tfloat val = p2gbuffer[channelid][static_cast(static_cast(cx) + (local_block_id & 4 ? config::G_BLOCKSIZE : 0))][static_cast(static_cast(cy) + (local_block_id & 2 ? config::G_BLOCKSIZE : 0))][static_cast(static_cast(cz) + (local_block_id & 1 ? config::G_BLOCKSIZE : 0))];\n\t\tif(channelid == 0) {\n\t\t\tatomicAdd(&next_grid.ch(_0, blockno).val_1d(_0, c), val);\n\t\t} else if(channelid == 1) {\n\t\t\tatomicAdd(&next_grid.ch(_0, blockno).val_1d(_1, c), val);\n\t\t} else if(channelid == 2) {\n\t\t\tatomicAdd(&next_grid.ch(_0, blockno).val_1d(_2, c), val);\n\t\t} else {\n\t\t\tatomicAdd(&next_grid.ch(_0, blockno).val_1d(_3, c), val);\n\t\t}\n\t}\n}\n\ntemplate\n__global__ void mark_active_grid_blocks(uint32_t block_count, const Grid grid, int* marks) {\n\tconst auto idx\t = blockIdx.x * blockDim.x + threadIdx.x;\n\tconst int blockno = static_cast(idx / config::G_BLOCKVOLUME);\n\tconst int cellno = static_cast(idx % config::G_BLOCKVOLUME);\n\tif(blockno >= block_count) {\n\t\treturn;\n\t}\n\n\t//If the grid cell has a mass mark it as active\n\tif(grid.ch(_0, blockno).val_1d(_0, cellno) != 0.0f) {\n\t\tmarks[blockno] = 1;\n\t}\n}\n\n__global__ void mark_active_particle_blocks(uint32_t block_count, const int* __restrict__ particle_bucket_sizes, int* marks) {\n\tconst std::size_t blockno = static_cast(blockIdx.x) * blockDim.x + threadIdx.x;\n\tif(blockno >= block_count) {\n\t\treturn;\n\t}\n\n\t//If the particle bucket has particles marke it as active\n\tif(particle_bucket_sizes[blockno] > 0) {\n\t\tmarks[blockno] = 1;\n\t}\n}\n\ntemplate\n__global__ void update_partition(uint32_t block_count, const int* __restrict__ source_nos, const Partition partition, Partition next_partition) {\n\tconst std::size_t blockno = static_cast(blockIdx.x) * blockDim.x + threadIdx.x;\n\tif(blockno >= block_count) {\n\t\treturn;\n\t}\n\n\tconst uint32_t source_no\t\t\t= source_nos[blockno];\n\tconst auto source_blockid\t\t\t= partition.active_keys[source_no];\n\tnext_partition.active_keys[blockno] = source_blockid;\n\tnext_partition.reinsert(static_cast(blockno));\n}\n\ntemplate\n__global__ void update_buckets(uint32_t block_count, const int* __restrict__ source_nos, const ParticleBuffer particle_buffer, ParticleBuffer next_particle_buffer) {\n\t__shared__ std::size_t source_no[1];//NOLINT(modernize-avoid-c-arrays) Cannot declare shared memory as std::array?\n\tconst std::size_t blockno = blockIdx.x;\n\tif(blockno >= block_count) {\n\t\treturn;\n\t}\n\n\t//Copy size and set source_no\n\tif(threadIdx.x == 0) {\n\t\t//Index of block in old layout\n\t\tsource_no[0]\t\t\t\t\t\t\t\t\t\t= source_nos[blockno];\n\t\tnext_particle_buffer.particle_bucket_sizes[blockno] = particle_buffer.particle_bucket_sizes[source_no[0]];\n\t}\n\t__syncthreads();\n\n\t//Copy buckets\n\tconst auto particle_counts = next_particle_buffer.particle_bucket_sizes[blockno];\n\tfor(int particle_id_in_block = static_cast(threadIdx.x); particle_id_in_block < particle_counts; particle_id_in_block += static_cast(blockDim.x)) {\n\t\tnext_particle_buffer.blockbuckets[blockno * config::G_PARTICLE_NUM_PER_BLOCK + particle_id_in_block] = particle_buffer.blockbuckets[source_no[0] * config::G_PARTICLE_NUM_PER_BLOCK + particle_id_in_block];\n\t}\n}\n\ntemplate\n__global__ void copy_selected_grid_blocks(const ivec3* __restrict__ prev_blockids, const Partition partition, const int* __restrict__ marks, Grid prev_grid, Grid grid) {\n\tconst auto blockid = prev_blockids[blockIdx.x];\n\n\t//If the block is marked as active and if it is found in the new partition, copy the values from the old grid\n\tif(marks[blockIdx.x]) {\n\t\tconst auto blockno = partition.query(blockid);\n\t\tif(blockno == -1) {\n\t\t\treturn;\n\t\t}\n\n\t\tconst auto sourceblock\t\t\t\t= prev_grid.ch(_0, blockIdx.x);\n\t\tauto targetblock\t\t\t\t\t= grid.ch(_0, blockno);\n\t\ttargetblock.val_1d(_0, threadIdx.x) = sourceblock.val_1d(_0, threadIdx.x);\n\t\ttargetblock.val_1d(_1, threadIdx.x) = sourceblock.val_1d(_1, threadIdx.x);\n\t\ttargetblock.val_1d(_2, threadIdx.x) = sourceblock.val_1d(_2, threadIdx.x);\n\t\ttargetblock.val_1d(_3, threadIdx.x) = sourceblock.val_1d(_3, threadIdx.x);\n\t}\n}\n\ntemplate\n__global__ void check_table(uint32_t block_count, Partition partition) {\n\tuint32_t blockno = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(blockno >= block_count) {\n\t\treturn;\n\t}\n\tauto blockid = partition.active_keys[blockno];\n\tif(partition.query(blockid) != blockno) {\n\t\tprintf(\"FUCK, partition table is wrong!\\n\");\n\t}\n}\n\ntemplate\n__global__ void sum_grid_mass(Grid grid, float* sum) {\n\tatomicAdd(sum, grid.ch(_0, blockIdx.x).val_1d(_0, threadIdx.x));\n}\n\n__global__ void sum_particle_counts(uint32_t count, int* __restrict__ counts, int* sum) {\n\tauto idx = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(idx >= count) {\n\t\treturn;\n\t}\n\tatomicAdd(sum, counts[idx]);\n}\n\ntemplate\n__global__ void check_partition(uint32_t block_count, Partition partition) {\n\tint idx = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(idx >= block_count) {\n\t\treturn;\n\t}\n\tivec3 blockid = partition.active_keys[idx];\n\tif(blockid[0] == 0 || blockid[1] == 0 || blockid[2] == 0) {\n\t\tprintf(\"\\tDAMN, encountered zero block record\\n\");\n\t}\n\tif(partition.query(blockid) != idx) {\n\t\tint id\t = partition.query(blockid);\n\t\tivec3 bid = partition.active_keys[id];\n\t\tprintf(\n\t\t\t\"\\t\\tcheck partition %d, (%d, %d, %d), feedback index %d, (%d, %d, \"\n\t\t\t\"%d)\\n\",\n\t\t\tidx,\n\t\t\t(int) blockid[0],\n\t\t\t(int) blockid[1],\n\t\t\t(int) blockid[2],\n\t\t\tid,\n\t\t\tbid[0],\n\t\t\tbid[1],\n\t\t\tbid[2]\n\t\t);\n\t}\n}\n\ntemplate\n__global__ void check_partition_domain(uint32_t block_count, int did, Domain const domain, Partition partition) {\n\tint idx = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(idx >= block_count) {\n\t\treturn;\n\t}\n\tivec3 blockid = partition.active_keys[idx];\n\tif(domain.inside(blockid)) {\n\t\tprintf(\"%d-th block (%d, %d, %d) is in domain[%d] (%d, %d, %d)-(%d, %d, %d)\\n\", idx, blockid[0], blockid[1], blockid[2], did, domain._min[0], domain._min[1], domain._min[2], domain._max[0], domain._max[1], domain._max[2]);\n\t}\n}\n\ntemplate\n__global__ void retrieve_particle_buffer(Partition partition, Partition prev_partition, ParticleBuffer particle_buffer, ParticleBuffer next_particle_buffer, ParticleArray particle_array, int* parcount) {\n\tconst int particle_counts\t= next_particle_buffer.particle_bucket_sizes[blockIdx.x];\n\tconst ivec3 blockid\t\t\t= partition.active_keys[blockIdx.x];\n\tconst auto advection_bucket = next_particle_buffer.blockbuckets + blockIdx.x * config::G_PARTICLE_NUM_PER_BLOCK;\n\n\t// auto particle_offset = particle_buffer.bin_offsets[blockIdx.x];\n\tfor(int particle_id_in_block = static_cast(threadIdx.x); particle_id_in_block < particle_counts; particle_id_in_block += static_cast(blockDim.x)) {\n\t\t//Fetch advection (direction at high bits, particle in in cell at low bits)\n\t\tconst auto advect = advection_bucket[particle_id_in_block];\n\n\t\t//Retrieve the direction (first stripping the particle id by division)\n\t\tivec3 source_blockid;\n\t\tdir_components(advect / config::G_PARTICLE_NUM_PER_BLOCK, source_blockid.data_arr());\n\n\t\t//Retrieve the particle id by AND for lower bits\n\t\tconst auto source_pidib = advect % config::G_PARTICLE_NUM_PER_BLOCK;\n\n\t\t//Get global index by adding the blockid\n\t\tsource_blockid += blockid;\n\n\t\t//Get block from partition\n\t\tconst auto advection_source_blockno_from_partition = prev_partition.query(source_blockid);\n\n\t\t//Get bin from particle buffer\n\t\tconst auto source_bin = particle_buffer.ch(_0, particle_buffer.bin_offsets[advection_source_blockno_from_partition] + source_pidib / config::G_BIN_CAPACITY);\n\n\t\t//Calculate particle id in destination buffer\n\t\tconst auto particle_id = atomicAdd(parcount, 1);\n\n\t\t//Copy position to destination buffer\n\t\tparticle_array.val(_0, particle_id) = source_bin.val(_0, source_pidib % config::G_BIN_CAPACITY);\n\t\tparticle_array.val(_1, particle_id) = source_bin.val(_1, source_pidib % config::G_BIN_CAPACITY);\n\t\tparticle_array.val(_2, particle_id) = source_bin.val(_2, source_pidib % config::G_BIN_CAPACITY);\n\t}\n}\n//NOLINTEND(cppcoreguidelines-pro-bounds-pointer-arithmetic, readability-magic-numbers, readability-identifier-naming, misc-definitions-in-headers)\n}// namespace mn\n\n#endif" }, { "path": "Projects/GMPM/particle_buffer.cuh", "content": "#ifndef PARTICLE_BUFFER_CUH\n#define PARTICLE_BUFFER_CUH\n#include \n\n#include \n\n#include \"hash_table.cuh\"\n#include \"mgmpm_kernels.cuh\"\n#include \"settings.h\"\n#include \"utility_funcs.hpp\"\n\n//NOLINTNEXTLINE(cppcoreguidelines-macro-usage) Macro usage necessary here for preprocessor if\n#define PRINT_NEGATIVE_BLOGNOS 1\n\nnamespace mn {\n\nusing ParticleBinDomain\t = AlignedDomain;\nusing ParticleBufferDomain = CompactDomain;\nusing ParticleArrayDomain = CompactDomain;\n//NOLINTBEGIN(cppcoreguidelines-avoid-non-const-global-variables, readability-identifier-naming) Check is buggy and reporst variable errors fro template arguments\nusing particle_bin4_ = Structural, ParticleBinDomain, attrib_layout::SOA, f32_, f32_, f32_, f32_>;\t\t\t\t\t\t\t\t\t\t\t\t\t\t///< J, pos\nusing particle_bin12_ = Structural, ParticleBinDomain, attrib_layout::SOA, f32_, f32_, f32_, f32_, f32_, f32_, f32_, f32_, f32_, f32_, f32_, f32_>;\t\t///< pos, F\nusing particle_bin13_ = Structural, ParticleBinDomain, attrib_layout::SOA, f32_, f32_, f32_, f32_, f32_, f32_, f32_, f32_, f32_, f32_, f32_, f32_, f32_>;///< pos, F, logJp\n//NOLINTEND(cppcoreguidelines-avoid-non-const-global-variables, readability-identifier-naming)\n\ntemplate\nstruct particle_bin_;\ntemplate<>\nstruct particle_bin_ : particle_bin4_ {};\ntemplate<>\nstruct particle_bin_ : particle_bin12_ {};\ntemplate<>\nstruct particle_bin_ : particle_bin13_ {};\ntemplate<>\nstruct particle_bin_ : particle_bin13_ {};\n\n//NOLINTBEGIN(cppcoreguidelines-avoid-non-const-global-variables, readability-identifier-naming) Check is buggy and reporst variable errors fro template arguments\ntemplate\nusing particle_buffer_ = Structural, ParticleBufferDomain, attrib_layout::AOS, ParticleBin>;\nusing particle_array_ = Structural, ParticleArrayDomain, attrib_layout::AOS, f32_, f32_, f32_>;\n//NOLINTEND(cppcoreguidelines-avoid-non-const-global-variables, readability-identifier-naming)\n\ntemplate\nstruct ParticleBufferImpl : Instance>> {\n\tstatic constexpr MaterialE MATERIAL_TYPE = Mt;\n\tusing base_t\t\t\t\t\t\t\t = Instance>>;\n\n\tstd::size_t num_active_blocks;\n\tint* cell_particle_counts;\n\tint* particle_bucket_sizes;\n\tint* cellbuckets;\n\tint* blockbuckets;\n\tint* bin_offsets;\n\n\ttemplate\n\tParticleBufferImpl(Allocator allocator, std::size_t count)\n\t\t: base_t {spawn>, orphan_signature>(allocator, count)}\n\t\t, num_active_blocks {0}\n\t\t, cell_particle_counts {nullptr}\n\t\t, particle_bucket_sizes {nullptr}\n\t\t, cellbuckets {nullptr}\n\t\t, blockbuckets {nullptr}\n\t\t, bin_offsets {nullptr} {}\n\n\ttemplate\n\tvoid check_capacity(Allocator allocator, std::size_t capacity) {\n\t\tif(capacity > this->capacity) {\n\t\t\tthis->resize(allocator, capacity);\n\t\t}\n\t}\n\n\ttemplate\n\tvoid reserve_buckets(Allocator allocator, std::size_t num_block_count) {\n\t\tif(bin_offsets) {\n\t\t\tallocator.deallocate(cell_particle_counts, sizeof(int) * num_active_blocks * config::G_BLOCKVOLUME);\n\t\t\tallocator.deallocate(particle_bucket_sizes, sizeof(int) * num_active_blocks);\n\t\t\tallocator.deallocate(cellbuckets, sizeof(int) * num_active_blocks * config::G_BLOCKVOLUME * config::G_MAX_PARTICLES_IN_CELL);\n\t\t\tallocator.deallocate(blockbuckets, sizeof(int) * num_active_blocks * config::G_PARTICLE_NUM_PER_BLOCK);\n\t\t\tallocator.deallocate(bin_offsets, sizeof(int) * num_active_blocks);\n\t\t}\n\t\tnum_active_blocks\t = num_block_count;\n\t\tcell_particle_counts = static_cast(allocator.allocate(sizeof(int) * num_active_blocks * config::G_BLOCKVOLUME));\n\t\tparticle_bucket_sizes = static_cast(allocator.allocate(sizeof(int) * num_active_blocks));\n\t\tcellbuckets\t\t\t = static_cast(allocator.allocate(sizeof(int) * num_active_blocks * config::G_BLOCKVOLUME * config::G_MAX_PARTICLES_IN_CELL));\n\t\tblockbuckets\t\t = static_cast(allocator.allocate(sizeof(int) * num_active_blocks * config::G_PARTICLE_NUM_PER_BLOCK));\n\t\tbin_offsets\t\t\t = static_cast(allocator.allocate(sizeof(int) * num_active_blocks));\n\t\treset_ppcs();\n\t}\n\n\tvoid reset_ppcs() {\n\t\tcheck_cuda_errors(cudaMemset(cell_particle_counts, 0, sizeof(int) * num_active_blocks * config::G_BLOCKVOLUME));\n\t}\n\n\tvoid copy_to(ParticleBufferImpl& other, std::size_t block_count, cudaStream_t stream) const {\n\t\tcheck_cuda_errors(cudaMemcpyAsync(other.bin_offsets, bin_offsets, sizeof(int) * (block_count + 1), cudaMemcpyDefault, stream));\n\t\tcheck_cuda_errors(cudaMemcpyAsync(other.particle_bucket_sizes, particle_bucket_sizes, sizeof(int) * block_count, cudaMemcpyDefault, stream));\n\t}\n\n\t//FIXME: passing kjey_t here might cause problems because cuda is buggy\n\t__forceinline__ __device__ void add_advection(Partition<1>& table, Partition<1>::key_t cellid, int dirtag, int particle_id_in_block) noexcept {\n\t\tconst Partition<1>::key_t blockid = cellid / static_cast(config::G_BLOCKSIZE);\n\t\tconst int blockno\t\t\t\t = table.query(blockid);\n\n\t\t//If block does not yet exist, print message and return (particle will be lost).\n\t\tif(blockno == -1) {\n#if PRINT_NEGATIVE_BLOGNOS\n\t\t\tstd::array offset {};\n\t\t\tdir_components(dirtag, offset);\n\t\t\t//NOLINTNEXTLINE(cppcoreguidelines-pro-type-vararg, readability-magic-numbers) Cuda has no other way to print; Numbers are array indices to be printed\n\t\t\tprintf(\"loc(%d, %d, %d) dir(%d, %d, %d) particle_id_in_block(%d)\\n\", cellid[0], cellid[1], cellid[2], offset[0], offset[1], offset[2], particle_id_in_block);\n#endif\n\t\t\treturn;\n\t\t}\n\t\t//Store the particle id and its offset in the dst cell bucket\n\n\t\t//NOLINTNEXTLINE(readability-magic-numbers) Numbers are array indices to be printed\n\t\tconst int cellno = ((cellid[0] & config::G_BLOCKMASK) << (config::G_BLOCKBITS << 1)) | ((cellid[1] & config::G_BLOCKMASK) << config::G_BLOCKBITS) | (cellid[2] & config::G_BLOCKMASK);\n\t\t//NOLINTNEXTLINE(cppcoreguidelines-pro-bounds-pointer-arithmetic) Cuda does not yet support std::span\n\t\tconst int particle_id_in_cell = atomicAdd(cell_particle_counts + static_cast(blockno) * config::G_BLOCKVOLUME + cellno, 1);\n\n\t\t//If no space is left, don't store the particle\n\t\tif(particle_id_in_cell >= config::G_MAX_PARTICLES_IN_CELL) {\n\t\t\t//Reduce count again\n\t\t\t//NOLINTNEXTLINE(cppcoreguidelines-pro-bounds-pointer-arithmetic) Cuda does not yet support std::span\n\t\t\tatomicSub(cell_particle_counts + static_cast(blockno) * config::G_BLOCKVOLUME + cellno, 1);\n#if PRINT_CELL_OVERFLOW\n\t\t\t//NOLINTNEXTLINE(cppcoreguidelines-pro-type-vararg, readability-magic-numbers) Cuda has no other way to print; Numbers are array indices to be printed\n\t\t\tprintf(\"No space left in cell: block(%d), cell(%d)\\n\", blockno, cellno);\n#endif\n\t\t\treturn;\n\t\t}\n\n\t\t//NOLINTNEXTLINE(cppcoreguidelines-pro-bounds-pointer-arithmetic) Cuda does not yet support std::span\n\t\tcellbuckets[blockno * config::G_PARTICLE_NUM_PER_BLOCK + cellno * config::G_MAX_PARTICLES_IN_CELL + particle_id_in_cell] = (dirtag * config::G_PARTICLE_NUM_PER_BLOCK) | particle_id_in_block;\n\t}\n};\n\n//NOTE: In subsequent classes some parameters are actually const and static, but they are nit declared as such to allow consistent access to the members\n//TODO: Maybe write accessors; Maybe create common baseclass(es) for accessing the parameters\n\ntemplate\nstruct ParticleBuffer;\ntemplate<>\nstruct ParticleBuffer : ParticleBufferImpl {\n\tusing base_t = ParticleBufferImpl;\n\n\t//NOLINTBEGIN(readability-magic-numbers) Parameter definitions\n\tfloat rho\t\t= config::DENSITY;\n\tfloat volume\t= (1.0f / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / config::MODEL_PPC);\n\tfloat mass\t\t= (config::DENSITY / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / config::MODEL_PPC);\n\tfloat bulk\t\t= 4e4;\n\tfloat gamma\t\t= 7.15f;//Penalize large deviations from incompressibility\n\tfloat viscosity = 0.01f;\n\n\tvoid update_parameters(float density, float vol, float b, float g, float v) {\n\t\trho\t\t = density;\n\t\tvolume\t = vol;\n\t\tmass\t = volume * density;\n\t\tbulk\t = b;\n\t\tgamma\t = g;\n\t\tviscosity = v;\n\t}\n\t//NOLINTEND(readability-magic-numbers)\n\n\ttemplate\n\tParticleBuffer(Allocator allocator, std::size_t count)\n\t\t: base_t {allocator, count} {}\n};\n\ntemplate<>\nstruct ParticleBuffer : ParticleBufferImpl {\n\tusing base_t = ParticleBufferImpl;\n\n\t//NOLINTBEGIN(readability-magic-numbers) Parameter definitions\n\tfloat rho\t = config::DENSITY;\n\tfloat volume = (10.f / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / config::MODEL_PPC);\n\tfloat mass\t = (config::DENSITY / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / config::MODEL_PPC);\n\tfloat e\t\t = config::YOUNGS_MODULUS;\n\tfloat nu\t = config::POISSON_RATIO;\n\tfloat lambda = config::YOUNGS_MODULUS * config::POISSON_RATIO / ((1 + config::POISSON_RATIO) * (1 - 2 * config::POISSON_RATIO));\n\tfloat mu\t = config::YOUNGS_MODULUS / (2 * (1 + config::POISSON_RATIO));\n\n\tvoid update_parameters(float density, float vol, float e, float nu) {\n\t\trho\t = density;\n\t\tvolume = vol;\n\t\tmass = volume * density;\n\t\tlambda = e * nu / ((1 + nu) * (1 - 2 * nu));\n\t\tmu\t = e / (2 * (1 + nu));\n\t}\n\t//NOLINTEND(readability-magic-numbers)\n\n\ttemplate\n\tParticleBuffer(Allocator allocator, std::size_t count)\n\t\t: base_t {allocator, count} {}\n};\n\ntemplate<>\nstruct ParticleBuffer : ParticleBufferImpl {\n\tusing base_t = ParticleBufferImpl;\n\n\t//NOLINTBEGIN(readability-magic-numbers) Parameter definitions; consistent naming\n\tfloat rho\t = config::DENSITY;\n\tfloat volume = (10.f / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / config::MODEL_PPC);\n\tfloat mass\t = (config::DENSITY / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / config::MODEL_PPC);\n\tfloat r\t\t = config::YOUNGS_MODULUS;\n\tfloat nu\t = config::POISSON_RATIO;\n\tfloat lambda = config::YOUNGS_MODULUS * config::POISSON_RATIO / ((1 + config::POISSON_RATIO) * (1 - 2 * config::POISSON_RATIO));\n\tfloat mu\t = config::YOUNGS_MODULUS / (2 * (1 + config::POISSON_RATIO));\n\n\tstatic constexpr float LOG_JP_0 = 0.0f;\n\tfloat friction_angle\t\t\t= 30.f;\n\tfloat cohesion\t\t\t\t\t= 0.0f;\n\tfloat beta\t\t\t\t\t\t= 1.0f;\n\t// std::sqrt(2.f/3.f) * 2.f * std::sin(30.f/180.f*3.141592741f)\n\t// \t\t\t\t\t\t/ (3.f -\n\t// std::sin(30.f/180.f*3.141592741f))\n\tfloat yield_surface\t = 0.816496580927726f * 2.f * 0.5f / (3.f - 0.5f);\n\tbool volume_correction = true;\n\t//NOLINTEND(readability-magic-numbers)\n\n\ttemplate\n\tParticleBuffer(Allocator allocator, std::size_t count)\n\t\t: base_t {allocator, count} {}\n};\n\ntemplate<>\nstruct ParticleBuffer : ParticleBufferImpl {\n\tusing base_t = ParticleBufferImpl;\n\n\t//NOLINTBEGIN(readability-magic-numbers) Parameter definitions\n\tfloat rho\t = config::DENSITY;\n\tfloat volume = (1.0f / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / config::MODEL_PPC);\n\tfloat mass\t = (config::DENSITY / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / config::MODEL_PPC);\n\tfloat e\t\t = config::YOUNGS_MODULUS;\n\tfloat nu\t = config::POISSON_RATIO;\n\tfloat lambda = config::YOUNGS_MODULUS * config::POISSON_RATIO / ((1 + config::POISSON_RATIO) * (1 - 2 * config::POISSON_RATIO));\n\tfloat mu\t = config::YOUNGS_MODULUS / (2 * (1 + config::POISSON_RATIO));\n\n\tfloat friction_angle\t\t\t= 45.f;\n\tfloat bm\t\t\t\t\t\t= 2.f / 3.f * (config::YOUNGS_MODULUS / (2 * (1 + config::POISSON_RATIO))) + (config::YOUNGS_MODULUS * config::POISSON_RATIO / ((1 + config::POISSON_RATIO) * (1 - 2 * config::POISSON_RATIO)));///< bulk modulus, kappa\n\tfloat xi\t\t\t\t\t\t= 0.8f;\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t///< hardening factor\n\tstatic constexpr float LOG_JP_0 = -0.01f;\n\tfloat beta\t\t\t\t\t\t= 0.5f;\n\tfloat mohr_columb_friction\t\t= 0.503599787772409;//< sqrt((T)2 / (T)3) * (T)2 * sin_phi / ((T)3 - sin_phi);\n\tfloat m\t\t\t\t\t\t\t= 1.850343771924453;//< mohr_columb_friction * (T)dim / sqrt((T)2 / ((T)6 - dim));\n\tfloat msqr\t\t\t\t\t\t= 3.423772074299613;\n\tbool hardening_on\t\t\t\t= true;\n\n\tvoid update_parameters(float density, float vol, float e, float nu, float be, float x) {\n\t\trho\t = density;\n\t\tvolume = vol;\n\t\tmass = volume * density;\n\t\tlambda = e * nu / ((1 + nu) * (1 - 2 * nu));\n\t\tmu\t = e / (2 * (1 + nu));\n\t\tbm\t = 2.f / 3.f * (e / (2 * (1 + nu))) + (e * nu / ((1 + nu) * (1 - 2 * nu)));\n\t\tbeta = be;\n\t\txi\t = x;\n\t}\n\t//NOLINTEND(readability-magic-numbers)\n\n\ttemplate\n\tParticleBuffer(Allocator allocator, std::size_t count)\n\t\t: base_t {allocator, count} {}\n};\n\n/// conversion\n/// http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2018/p0608r3.html\nusing particle_buffer_t = variant, ParticleBuffer, ParticleBuffer, ParticleBuffer>;\n\nstruct ParticleArray : Instance {\n\tusing base_t = Instance;\n\n\tParticleArray() = default;\n\texplicit ParticleArray(base_t&& instance)//NOLINT(cppcoreguidelines-rvalue-reference-param-not-moved) Clang say, that std::move has no effect here\n\t\t: base_t(instance) {}\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Projects/GMPM/partition_domain.h", "content": "#ifndef __PARTITION_DOMAIN_H_\n#define __PARTITION_DOMAIN_H_\n#include \n#include \n\nnamespace mn {\n\ntemplate\nstruct partition_domain {\n\tusing index = Tn[dim];\n\n\ttemplate\n\tconstexpr bool inside(Index&& id) const noexcept {\n\t\treturn self().inside(std::forward(id));\n\t}\n\ttemplate\n\tconstexpr bool within(Index&& id, Offset&& l, Offset&& u) const noexcept {\n\t\treturn self().within(std::forward(id), std::forward(l), std::forward(u));\n\t}\n\n protected:\n\tauto& self() noexcept {\n\t\treturn static_cast(*this);\n\t}\n};\n\ntemplate\nstruct box_domain : partition_domain, Tn, dim> {\n\tusing base_t = partition_domain, Tn, dim>;\n\tusing index\t = typename base_t::index;\n\tconstexpr box_domain() noexcept {}\n\tconstexpr box_domain(index lower, index upper) {\n\t\tfor(int d = 0; d < dim; ++d) {\n\t\t\t_min[d] = lower[d];\n\t\t\t_max[d] = upper[d];\n\t\t}\n\t}\n\tconstexpr box_domain(vec lower, vec upper) {\n\t\tfor(int d = 0; d < dim; ++d) {\n\t\t\t_min[d] = lower[d];\n\t\t\t_max[d] = upper[d];\n\t\t}\n\t}\n\ttemplate\n\tconstexpr bool inside(Index&& id) const noexcept {\n\t\tfor(int d = 0; d < dim; ++d)\n\t\t\tif(id[d] < _min[d] || id[d] > _max[d])\n\t\t\t\treturn false;\n\t\treturn true;\n\t}\n\ttemplate\n\tconstexpr bool within(Index&& id, Offset&& l, Offset&& u) const noexcept {\n\t\tfor(int d = 0; d < dim; ++d)\n\t\t\tif(id[d] < _min[d] + l[d] || id[d] > _max[d] + u[d])\n\t\t\t\treturn false;\n\t\treturn true;\n\t}\n\tindex _min, _max;\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Projects/GMPM/scenes/scene.json", "content": "{\n\t\"simulation\": {\n\t\t\"gpuid\": 0,\n\t\t\"fps\": 1200,\n\t\t\"frames\": 120,\n\t\t\"default_dt\": 5e-6\n\t},\n\t\"models\": [\n\t\t{\n\t\t\t\"type\": \"particle\",\n\t\t\t\"file\": \"two_dragons.sdf\",\n\t\t\t\"constitutive\": \"jfluid\",\n\t\t\t\"volume\": 7.4505806e-9,\n\t\t\t\"rho\": 1e3,\n\t\t\t\"bulk_modulus\": 4e4,\n\t\t\t\"gamma\": 7.15,\n\t\t\t\"viscosity\": 0.01,\n\t\t\t\"offset\": [\n\t\t\t\t0.1,\n\t\t\t\t0.1,\n\t\t\t\t0.1\n\t\t\t],\n\t\t\t\"span\": [\n\t\t\t\t1.0,\n\t\t\t\t1.0,\n\t\t\t\t1.0\n\t\t\t],\n\t\t\t\"velocity\": [\n\t\t\t\t0.0,\n\t\t\t\t-1.0,\n\t\t\t\t0.0\n\t\t\t]\n\t\t},\n\t\t{\n\t\t\t\"type\": \"particle\",\n\t\t\t\"file\": \"two_dragons.sdf\",\n\t\t\t\"constitutive\": \"fixed_corotated\",\n\t\t\t\"volume\": 7.4505806e-9,\n\t\t\t\"rho\": 1e3,\n\t\t\t\"youngs_modulus\": 1e7,\n\t\t\t\"poisson_ratio\": 0.4,\n\t\t\t\"offset\": [\n\t\t\t\t0.2,\n\t\t\t\t0.1,\n\t\t\t\t0.1\n\t\t\t],\n\t\t\t\"span\": [\n\t\t\t\t1.0,\n\t\t\t\t1.0,\n\t\t\t\t1.0\n\t\t\t],\n\t\t\t\"velocity\": [\n\t\t\t\t0.0,\n\t\t\t\t-1.0,\n\t\t\t\t0.0\n\t\t\t]\n\t\t},\n\t\t{\n\t\t\t\"type\": \"particle\",\n\t\t\t\"file\": \"two_dragons.sdf\",\n\t\t\t\"constitutive\": \"sand\",\n\t\t\t\"offset\": [\n\t\t\t\t0.2,\n\t\t\t\t0.1,\n\t\t\t\t0.2\n\t\t\t],\n\t\t\t\"span\": [\n\t\t\t\t1.0,\n\t\t\t\t1.0,\n\t\t\t\t1.0\n\t\t\t],\n\t\t\t\"velocity\": [\n\t\t\t\t0.0,\n\t\t\t\t-1.0,\n\t\t\t\t0.0\n\t\t\t]\n\t\t}\n\t]\n}" }, { "path": "Projects/GMPM/settings.h", "content": "#ifndef SETTINGS_H\n#define SETTINGS_H\n#include \n#include \n\n#include \n\n//NOLINTNEXTLINE(cppcoreguidelines-macro-usage) Macro usage necessary here for preprocessor if\n#define PRINT_CELL_OVERFLOW 0//TODO: Move to another place\n\nnamespace mn {\n\nusing ivec3\t = vec;\nusing vec3\t = vec;\nusing vec9\t = vec;\nusing vec3x3 = vec;\nusing vec3x4 = vec;\nusing vec3x3x3 = vec;\n\nusing Duration = std::chrono::duration;\n\n/// sand = Drucker Prager Plasticity, StvkHencky Elasticity\nenum class MaterialE {\n\tJ_FLUID = 0,\n\tFIXED_COROTATED,\n\tSAND,\n\tNACC,\n\tTOTAL\n};\n\n/// https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html, F.3.16.5\n/// benchmark setup\nnamespace config {\n\tconstexpr int G_DEVICE_COUNT = 1;\n\tconstexpr MaterialE get_material_type(int did) noexcept {\n\t\t(void) did;\n\n\t\treturn MaterialE::FIXED_COROTATED;\n\t}\n\tconstexpr int G_TOTAL_FRAME_CNT = 60;\n\tconstexpr int NUM_DIMENSIONS\t= 3;\n\n\tconstexpr int CUDA_WARP_SIZE = 32;\n\n\tconstexpr int GBPCB\t\t\t\t\t\t\t = 16;\n\tconstexpr int G_NUM_GRID_BLOCKS_PER_CUDA_BLOCK = GBPCB;\n\tconstexpr int G_NUM_WARPS_PER_GRID_BLOCK\t = 1;\n\tconstexpr int G_NUM_WARPS_PER_CUDA_BLOCK\t = GBPCB;//>= G_NUM_GRID_BLOCKS_PER_CUDA_BLOCK\n\tconstexpr int G_PARTICLE_BATCH_CAPACITY\t\t = 128;\n\n\tconstexpr float MODEL_PPC\t= 8.0f;\n\tconstexpr float G_MODEL_PPC = MODEL_PPC;\n\tconstexpr float CFL\t\t\t= 0.5f;\n\n\t// background_grid\n\tconstexpr float GRID_BLOCK_SPACING = 1.0f;\n\n\tconstexpr int BLOCK_BITS\t\t\t = 2;\n\tconstexpr int DOMAIN_BITS\t\t\t = 8;\n\tconstexpr float DXINV\t\t\t\t = (GRID_BLOCK_SPACING * (1 << DOMAIN_BITS));\n\tconstexpr int G_DOMAIN_BITS\t\t\t = DOMAIN_BITS;\n\tconstexpr int G_DOMAIN_SIZE\t\t\t = (1 << DOMAIN_BITS);\n\tconstexpr float G_BOUNDARY_CONDITION = 2.0;\n\tconstexpr float G_DX\t\t\t\t = 1.f / DXINV;\n\tconstexpr float G_DX_INV\t\t\t = DXINV;\n\tconstexpr float G_D_INV\t\t\t\t = 4.f * DXINV * DXINV;\n\tconstexpr int G_BLOCKBITS\t\t\t = BLOCK_BITS;\n\tconstexpr int G_BLOCKSIZE\t\t\t = (1 << BLOCK_BITS);\n\tconstexpr int G_BLOCKMASK\t\t\t = ((1 << BLOCK_BITS) - 1);\n\tconstexpr int G_BLOCKVOLUME\t\t\t = (1 << (BLOCK_BITS * 3));\n\tconstexpr int G_GRID_BITS\t\t\t = (DOMAIN_BITS - BLOCK_BITS);\n\tconstexpr int G_GRID_SIZE\t\t\t = (1 << (DOMAIN_BITS - BLOCK_BITS));\n\n\t// particle\n\tconstexpr int MAX_PARTICLES_IN_CELL\t = 128;\n\tconstexpr int G_MAX_PARTICLES_IN_CELL = MAX_PARTICLES_IN_CELL;\n\tconstexpr int G_BIN_CAPACITY\t\t = 32;\n\tconstexpr int G_PARTICLE_NUM_PER_BLOCK = (MAX_PARTICLES_IN_CELL * (1 << (BLOCK_BITS * 3)));\n\n\t// material parameters\n\tconstexpr float DENSITY\t\t = 1e3;\n\tconstexpr float YOUNGS_MODULUS = 5e3;\n\tconstexpr float POISSON_RATIO = 0.4f;\n\n\tconstexpr float G_GRAVITY = -9.8f;\n\n\t/// only used on host\n\tconstexpr int G_MAX_PARTICLE_NUM = 1000000;\n\tconstexpr int G_MAX_ACTIVE_BLOCK = 10000;/// 62500 bytes for active mask\n\tconstexpr std::size_t calc_particle_bin_count(std::size_t num_active_blocks) noexcept {\n\t\treturn num_active_blocks * (G_MAX_PARTICLES_IN_CELL * G_BLOCKVOLUME / G_BIN_CAPACITY);\n\t}\n\tconstexpr std::size_t G_MAX_PARTICLE_BIN = G_MAX_PARTICLE_NUM / G_BIN_CAPACITY;\n\tconstexpr std::size_t G_MAX_HALO_BLOCK\t = 4000;\n\n}// namespace config\n\nusing BlockDomain\t = CompactDomain;\nusing GridDomain\t = CompactDomain;\nusing GridBufferDomain = CompactDomain;\n\n}// namespace mn\n\n#endif" }, { "path": "Projects/GMPM/utility_funcs.hpp", "content": "#ifndef UTILITY_FUNCS_HPP\n#define UTILITY_FUNCS_HPP\n#include \"settings.h\"\n\nnamespace mn {\n\n//TODO: Maybe create parameters for some of this magic numbers\n//NOLINTBEGIN(readability-magic-numbers) Magic numbers are formula-specific\n/// assume p is already within kernel range [-1.5, 1.5]\nconstexpr vec3 bspline_weight(float p) {\n\tvec3 dw {0.0f, 0.0f, 0.0f};\n\tfloat d = p * config::G_DX_INV;///< normalized offset\n\tdw[0]\t= 0.5f * (1.5f - d) * (1.5f - d);\n\td -= 1.0f;\n\tdw[1] = 0.75f - d * d;\n\td\t = 0.5f + d;\n\tdw[2] = 0.5f * d * d;\n\treturn dw;\n}\n\nconstexpr ivec3 get_block_id(const std::array& position) {\n\treturn ivec3(static_cast(std::lround(position[0] * config::G_DX_INV)), static_cast(std::lround(position[1] * config::G_DX_INV)), static_cast(std::lround(position[2] * config::G_DX_INV)));\n}\n\nconstexpr int dir_offset(const std::array& d) {\n\treturn (d[0] + 1) * 9 + (d[1] + 1) * 3 + d[2] + 1;\n}\nconstexpr void dir_components(int dir, std::array& d) {\n\td[2] = (dir % 3) - 1;\n\td[1] = ((dir / 3) % 3) - 1;\n\td[0] = ((dir / 9) % 3) - 1;\n}\n//NOLINTEND(readability-magic-numbers) Magic numbers are formula-specific\n\n//NOLINTBEGIN(readability-magic-numbers) Magic numbers are formula-specific\nconstexpr Duration compute_dt(float max_vel, const Duration cur_time, const Duration next_time, const Duration dt_default) noexcept {\n\t//Choose dt such that particles with maximum velocity cannot move more than G_DX * CFL\n\t//This ensures CFL condition is satisfied\n\tDuration dt = dt_default;\n\tif(max_vel > 0.0f) {\n\t\tconst Duration new_dt(config::G_DX * config::CFL / max_vel);\n\t\tdt = std::min(new_dt, dt);\n\t}\n\n\t//If next_time - cur_time is smaller as current dt, use this.\n\tdt = std::min(dt, next_time - cur_time);\n\n\treturn dt;\n}\n//NOLINTEND(readability-magic-numbers) Magic numbers are formula-specific\n\n}// namespace mn\n\n#endif" }, { "path": "Projects/MGSP/CMakeLists.txt", "content": "if (CUDA_FOUND)\n\tadd_cuda_executable(mgsp)\n\t\n\ttarget_sources(mgsp \n\t\tPRIVATE mgsp.cu\n\t)\n\t\n\ttarget_link_libraries(mgsp \n\t\tPRIVATE mnio\n\t\t\t\t\tfmt\n\t)\n\n\t#Add headers as system headers\n\tget_target_property(HEADERS_FMT fmt INTERFACE_SYSTEM_INCLUDE_DIRECTORIES)\n\n\ttarget_include_directories(mgsp\n\t\tSYSTEM\n\t\tPRIVATE ${CMAKE_SOURCE_DIR}/Library\n\t\tPRIVATE ${HEADERS_FMT}\n\t)\n\nendif()" }, { "path": "Projects/MGSP/boundary_condition.cuh", "content": "#ifndef BOUNDARY_CONDITION_CUH\n#define BOUNDARY_CONDITION_CUH\n#include \n#include \n#include \n#include \n\n#include \n\n#include \"grid_buffer.cuh\"\n#include \"settings.h\"\n\nnamespace mn {\n\nusing block_signed_distance_field_ = Structural, BlockDomain, attrib_layout::SOA, f32_, f32_, f32_, f32_>;///< sdis, gradx, grady, gradz\nusing signed_distance_field_\t = Structural, GridDomain, attrib_layout::AOS, block_signed_distance_field_>;\n\nenum class BoundaryT {\n\tSTICKY,\n\tSLIP,\n\tSEPARATE\n};\n\n//NOLINTBEGIN(readability-magic-numbers) Parameter definitions and formulas\nstruct SignedDistanceGrid : Instance {\n\tusing base_t = Instance;\n\n\tvec3x3 rot_mat;\n\tvec3 trans;\n\tvec3 trans_vel;\n\tvec3 omega;\n\tfloat dsdt;\n\tfloat scale;\n\tfloat friction;\n\tBoundaryT type;\n\n\ttemplate\n\texplicit SignedDistanceGrid(Allocator allocator)\n\t\t: base_t {spawn(allocator)}\n\t\t, dsdt(0.0f)\n\t\t, scale(1.0f)\n\t\t, friction(0.3f)\n\t\t, type(BoundaryT::STICKY) {\n\t\trot_mat.set(0.0f);\n\t\trot_mat(0, 0) = rot_mat(1, 1) = rot_mat(2, 2) = 1.f;\n\t\ttrans.set(0.f);\n\t\ttrans_vel.set(0.f);\n\t\tomega.set(0.f);\n\t}\n\n\tvoid init(base_t& host_data, cudaStream_t stream) {\n\t\tcheck_cuda_errors(cudaMemcpyAsync(&this->ch(_0, 0, 0, 0).val_1d(_0, 0), &host_data.ch(_0, 0, 0, 0).val_1d(_0, 0), signed_distance_field_::base_t::size, cudaMemcpyDefault, stream));\n\t}\n\n\tconstexpr auto& self() noexcept {\n\t\treturn static_cast(*this);\n\t}\n\n\tconstexpr vec3 get_material_velocity(const vec3& x) {\n\t\tvec3 radius = x - trans;\n\t\tvec3 vel {};\n\t\tvec_cross_mul_vec_3d(vel.data_arr(), omega.data_arr(), radius.data_arr());\n\t\tvel += trans_vel;\n\t\treturn vel;\n\t}\n\n\tstatic __forceinline__ __device__ auto rot_angle_to_matrix(const float omega, const int dim) -> vec3x3 {\n\t\tvec3x3 res;\n\t\tres.set(0.0f);\n\t\tif(dim == 0) {\n\t\t\tres(0, 0) = 1;\n\t\t\tres(1, 1) = res(2, 2) = cosf(omega);\n\t\t\tres(2, 1) = res(1, 2) = sinf(omega);\n\t\t\tres(1, 2)\t\t\t = -res(1, 2);\n\t\t} else if(dim == 1) {\n\t\t\tres(1, 1) = 1;\n\t\t\tres(0, 0) = res(2, 2) = cosf(omega);\n\t\t\tres(2, 0) = res(0, 2) = sinf(omega);\n\t\t\tres(2, 0)\t\t\t = -res(2, 0);\n\t\t} else if(dim == 2) {\n\t\t\tres(2, 2) = 1;\n\t\t\tres(0, 0) = res(1, 1) = cosf(omega);\n\t\t\tres(1, 0) = res(0, 1) = sinf(omega);\n\t\t\tres(0, 1)\t\t\t = -res(0, 1);\n\t\t} else {\n\t\t\t//NOLINTNEXTLINE(cppcoreguidelines-pro-type-vararg) Cuda has no other way to print\n\t\t\tprintf(\"Unsupported dimension\");\n\t\t}\n\t\treturn res;\n\t}\n\n\tstatic constexpr auto vec3_cross_vec3(vec3 v1, vec3 v2) {\n\t\tvec3 res {v1[1] * v2[2] + v1[2] * v2[1], v1[2] * v2[0] + v1[0] * v2[2], v1[0] * v2[1] + v1[1] * v2[0]};\n\t\treturn res;\n\t}\n\n\t//< return signed distance value + set normal\n\t__forceinline__ __device__ float get_signed_distance_and_normal(const vec3& x, vec3& normal) {\n\t\t//< g_cid <=> global cell ID\n\t\tivec3 g_cid = (x / config::G_DX).cast();\n\n\t\t// 1. init\n\t\tfloat sdis_res {0.f};\n\t\tnormal.set(0.f);\n\n\t\t// 1.1 prepare\n\t\tstd::array, 2>, 2> w = {};//< linear interpolation weight\n\t\t{\n\t\t\tvec3 dis_lb\t\t\t\t\t\t\t\t = x - (g_cid.cast() * config::G_DX);//< distance to the left-corner node\n\t\t\tstd::array, 3> w_1d = {};\t\t\t\t\t\t\t\t\t\t//< 1d weight, [dim][node]\n\t\t\tfor(int d = 0; d < 3; ++d) {\n\t\t\t\tw_1d[d][0] = 1 - dis_lb[d] / config::G_DX;\n\t\t\t\tw_1d[d][1] = dis_lb[d] / config::G_DX;\n\t\t\t}\n\t\t\tfor(int i = 0; i < 2; ++i) {\n\t\t\t\tfor(int j = 0; j < 2; ++j) {\n\t\t\t\t\tfor(int k = 0; k < 2; ++k) {\n\t\t\t\t\t\tw[i][j][k] = w_1d[0][i] * w_1d[1][j] * w_1d[2][k];\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\n\t\t// 2. compute signed distance and normal\n\t\tfor(int i = 0; i < 2; ++i) {\n\t\t\tfor(int j = 0; j < 2; ++j) {\n\t\t\t\tfor(int k = 0; k < 2; ++k) {\n\t\t\t\t\tsdis_res += w[i][j][k] * (this->ch(_0, ((g_cid[0] + i) / config::G_BLOCKSIZE), ((g_cid[1] + j) / config::G_BLOCKSIZE), ((g_cid[2] + k) / config::G_BLOCKSIZE)).val(_0, (g_cid[0] + i) % config::G_BLOCKSIZE, (g_cid[1] + j) % config::G_BLOCKSIZE, (g_cid[2] + k) % config::G_BLOCKSIZE));\n\t\t\t\t\tnormal[0] += w[i][j][k] * (this->ch(_0, ((g_cid[0] + i) / config::G_BLOCKSIZE), ((g_cid[1] + j) / config::G_BLOCKSIZE), ((g_cid[2] + k) / config::G_BLOCKSIZE)).val(_1, (g_cid[0] + i) % config::G_BLOCKSIZE, (g_cid[1] + j) % config::G_BLOCKSIZE, (g_cid[2] + k) % config::G_BLOCKSIZE));\n\t\t\t\t\tnormal[1] += w[i][j][k] * (this->ch(_0, ((g_cid[0] + i) / config::G_BLOCKSIZE), ((g_cid[1] + j) / config::G_BLOCKSIZE), ((g_cid[2] + k) / config::G_BLOCKSIZE)).val(_2, (g_cid[0] + i) % config::G_BLOCKSIZE, (g_cid[1] + j) % config::G_BLOCKSIZE, (g_cid[2] + k) % config::G_BLOCKSIZE));\n\t\t\t\t\tnormal[2] += w[i][j][k] * (this->ch(_0, ((g_cid[0] + i) / config::G_BLOCKSIZE), ((g_cid[1] + j) / config::G_BLOCKSIZE), ((g_cid[2] + k) / config::G_BLOCKSIZE)).val(_3, (g_cid[0] + i) % config::G_BLOCKSIZE, (g_cid[1] + j) % config::G_BLOCKSIZE, (g_cid[2] + k) % config::G_BLOCKSIZE));\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\tnormal /= sqrtf(normal.l2NormSqr());\n\t\treturn sdis_res;\n\t}\n\t__forceinline__ __device__ bool query_sdf(vec3& normal, const vec3& x) {\n\t\tif(x[0] < config::G_BOUNDARY_CONDITION * config::G_DX * config::G_BLOCKSIZE || x[0] >= (GridDomain::range(_0) - config::G_BOUNDARY_CONDITION) * config::G_BLOCKSIZE * config::G_DX || x[1] < config::G_BOUNDARY_CONDITION * config::G_DX * config::G_BLOCKSIZE || x[1] >= (GridDomain::range(_1) - config::G_BOUNDARY_CONDITION) * config::G_BLOCKSIZE * config::G_DX || x[2] < config::G_BOUNDARY_CONDITION * config::G_DX * config::G_BLOCKSIZE || x[2] >= (GridDomain::range(_2) - config::G_BOUNDARY_CONDITION) * config::G_BLOCKSIZE * config::G_DX) {\n\t\t\treturn false;\n\t\t}\n\t\treturn get_signed_distance_and_normal(x, normal) <= 0.f;\n\t}\n\t//< detect if there is collision with the object, if there is, reset grid\n\t// velocity < call this inside grid update kernel\n\t/* Takes a position and its velocity,\n * project the grid velocity, //? [to check] and returns a normal if the\n * collision happened as a SLIP collsion.\n *\n * derivation:\n *\n * x = \\phi(X,t) = R(t)s(t)X+b(t)\n * X = \\phi^{-1}(x,t) = (1/s) R^{-1} (x-b)\n * V(X,t) = \\frac{\\partial \\phi}{\\partial t}\n * = R'sX + Rs'X + RsX' + b'\n * v(x,t) = V(\\phi^{-1}(x,t),t)\n * = R'R^{-1}(x-b) + (s'/s)(x-b) + RsX' + b'\n * = omega \\cross (x-b) + (s'/s)(x-b) + RsV + b'*/\n\t__forceinline__ __device__ void detect_and_resolve_collision(const ivec3 block_id, const ivec3 cell_id, float current_time, vec3& vel) {\n\t\tvec3 x_minustrans = (block_id * config::G_BLOCKSIZE + cell_id).cast() * config::G_DX - (trans + trans_vel * current_time);\n\t\t// material space\n\t\tvec3 x;\n\t\tvec3x3 current_rot_mat = rot_mat;\n\t\t{\n\t\t\tvec3 x0 = x_minustrans * (1.f / (1.f + dsdt * current_time));\n\n\t\t\tvec3x3 rot_tmp\t= SignedDistanceGrid::rot_angle_to_matrix(omega[0] * current_time, 0);\n\t\t\tvec3x3 prev_rot = current_rot_mat;\n\t\t\tmatrix_matrix_multiplication_3d(prev_rot.data_arr(), rot_tmp.data_arr(), current_rot_mat.data_arr());\n\n\t\t\trot_tmp\t = SignedDistanceGrid::rot_angle_to_matrix(omega[1] * current_time, 1);\n\t\t\tprev_rot = current_rot_mat;\n\t\t\tmatrix_matrix_multiplication_3d(prev_rot.data_arr(), rot_tmp.data_arr(), current_rot_mat.data_arr());\n\n\t\t\trot_tmp\t = SignedDistanceGrid::rot_angle_to_matrix(omega[2] * current_time, 2);\n\t\t\tprev_rot = current_rot_mat;\n\t\t\tmatrix_matrix_multiplication_3d(prev_rot.data_arr(), rot_tmp.data_arr(), current_rot_mat.data_arr());\n\t\t\tmat_t_mul_vec_3d(x.data_arr(), current_rot_mat.data_arr(), x0.data_arr());\n\t\t}\n\n\t\tx = x * scale + trans;\n\n\t\t//< enforce BC if inside LS\n\t\tvec3 obj_normal;\n\t\tbool hit = query_sdf(obj_normal, x);//< material space normal\n\t\tif(hit) {\n\t\t\t///< calculate object velocity in deformation space\n\t\t\tvec3 v_object = SignedDistanceGrid::vec3_cross_vec3(omega, x_minustrans);\n\t\t\tv_object += x_minustrans * (dsdt / scale);\n\t\t\t{\n\t\t\t\tvec3 rot_v;\n\t\t\t\tmatrix_vector_multiplication_3d(current_rot_mat.data_arr(), get_material_velocity(x).data_arr(), rot_v.data_arr());\n\t\t\t\tv_object += rot_v * scale + trans_vel;\n\t\t\t}\n\t\t\tvel -= v_object;\n\n\t\t\t/// STICKY\n\t\t\tif(type == BoundaryT::STICKY) {\n\t\t\t\tvel.set(0.0f);\n\t\t\t\t/// SLIP\n\t\t\t} else if(type == BoundaryT::SLIP) {\n\t\t\t\t{\n\t\t\t\t\tvec3 n;\n\t\t\t\t\tmatrix_vector_multiplication_3d(current_rot_mat.data_arr(), obj_normal.data_arr(), n.data_arr());\n\t\t\t\t\tobj_normal = n;\n\t\t\t\t}\n\t\t\t\tfloat v_dot_n = obj_normal.dot(vel);\n\t\t\t\tvel -= (obj_normal * v_dot_n);\n\t\t\t\tif(friction > 0.0f) {\n\t\t\t\t\tif(v_dot_n < 0) {\n\t\t\t\t\t\tfloat vel_norm = sqrtf(vel.l2NormSqr());\n\t\t\t\t\t\tif(-v_dot_n * friction < vel_norm) {\n\t\t\t\t\t\t\tvel += (vel / vel_norm * (v_dot_n * friction));\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\tvel.set(0.0f);\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t\t/// STICKY\n\t\t\telse if(type == BoundaryT::SEPARATE) {\n\t\t\t\tif(obj_normal[0] == 0.0f && obj_normal[1] == 0.0f && obj_normal[2] == 0.0f) {\n\t\t\t\t\tvel.set(0.0f);\n\t\t\t\t\treturn;\n\t\t\t\t}\n\t\t\t\t{\n\t\t\t\t\tvec3 n;\n\t\t\t\t\tmatrix_vector_multiplication_3d(current_rot_mat.data_arr(), obj_normal.data_arr(), n.data_arr());\n\t\t\t\t\tobj_normal = n;\n\t\t\t\t}\n\t\t\t\tfloat v_dot_n = obj_normal.dot(vel);\n\t\t\t\tif(v_dot_n < 0) {\n\t\t\t\t\tvel -= (obj_normal * v_dot_n);\n\t\t\t\t\tif(friction != 0) {\n\t\t\t\t\t\tfloat vel_norm = sqrtf(vel.l2NormSqr());\n\t\t\t\t\t\tif(-v_dot_n * friction < vel_norm) {\n\t\t\t\t\t\t\tvel += (vel / vel_norm * (v_dot_n * friction));\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\tvel.set(0.0f);\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t} else {\n\t\t\t\t//NOLINTNEXTLINE(cppcoreguidelines-pro-type-vararg) Cuda has no other way to print\n\t\t\t\tprintf(\"[ERROR] Wrong Boundary Type!\\n\");\n\t\t\t}\n\t\t\tvel += v_object;\n\t\t}\n\t}\n};\n//NOLINTEND(readability-magic-numbers)\n\ntemplate\ninline void fill_signed_distance_field(std::integral_constant chn, const std::vector& s_dis, Instance& host_data) {\n\tint inside_node_num = 0;\n\tfor(auto bx = 0; bx < GridDomain::range(_0); ++bx) {\n\t\tfor(auto by = 0; by < GridDomain::range(_1); ++by) {\n\t\t\tfor(auto bz = 0; bz < GridDomain::range(_2); ++bz) {\n\t\t\t\tauto sdis_block = host_data.ch(_0, bx, by, bz);\n\n\t\t\t\tfor(auto cx = 0; cx < config::G_BLOCKSIZE; ++cx) {\n\t\t\t\t\tauto i = bx * config::G_BLOCKSIZE + cx;\n\n\t\t\t\t\tfor(auto cy = 0; cy < config::G_BLOCKSIZE; ++cy) {\n\t\t\t\t\t\tauto j = by * config::G_BLOCKSIZE + cy;\n\n\t\t\t\t\t\tfor(auto cz = 0; cz < config::G_BLOCKSIZE; ++cz) {\n\t\t\t\t\t\t\tauto k\t\t\t\t\t\t\t= bz * config::G_BLOCKSIZE + cz;\n\t\t\t\t\t\t\tauto idx\t\t\t\t\t\t= (i * GridDomain::range(_1) * config::G_BLOCKSIZE * GridDomain::range(_2) * config::G_BLOCKSIZE) + (j * GridDomain::range(_2) * config::G_BLOCKSIZE) + k;\n\t\t\t\t\t\t\tsdis_block.val(chn, cx, cy, cz) = s_dis[idx];\n\t\t\t\t\t\t\tif(Chn == 0) {\n\t\t\t\t\t\t\t\tif(s_dis[idx] <= 0.0f) {\n\t\t\t\t\t\t\t\t\tinside_node_num++;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\tif(Chn == 0) {\n\t\tfmt::print(\n\t\t\t\"[Collision Object]\\n\\t[from saved signed_distance_field] \"\n\t\t\t\"Finish init signed distance buffer, inside node num = {}.\\n\",\n\t\t\tinside_node_num\n\t\t);\n\t} else {\n\t\tfmt::print(\n\t\t\t\"[Collision Object]\\n\\t[from saved signed_distance_field] \"\n\t\t\t\"Finish init signed distance gradient [{}].\\n\",\n\t\t\tChn\n\t\t);\n\t}\n}\n\ninline void init_from_signed_distance_file(const std::string& filename, vec resolution, Instance& host_data) {\n\tstd::string file_addr = std::string(AssetDirPath) + \"vdbSDF/\";\n\tstd::vector sdisf(resolution.prod());\n\tauto read_file = [&](const std::string& suffix) {\n\t\tstd::string file_path;\n\t\tfile_path.append(file_addr).append(filename).append(suffix);\n\t\tFILE* fn;\n\t\tfopen_s(&fn, file_path.c_str(), \"rb\");\n\t\tstd::size_t read_num = std::fread(static_cast(sdisf.data()), sizeof(float), sdisf.size(), fn);\n\t\tif(read_num != static_cast(resolution.prod())) {\n\t\t\tstd::cout << \"Error in loading file [\" << filename.c_str() << \"]: read in \" << read_num << \" entries, should be \" << resolution.prod() << std::endl;\n\t\t\tthrow std::runtime_error(\"Error occured while loading file\");\n\t\t}\n\t\tstd::fclose(fn);\n\t};\n\tread_file(\"_sdf.bin\");\n\tfill_signed_distance_field(_0, sdisf, host_data);\n\tread_file(\"_grad_0.bin\");\n\tfill_signed_distance_field(_1, sdisf, host_data);\n\tread_file(\"_grad_1.bin\");\n\tfill_signed_distance_field(_2, sdisf, host_data);\n\tread_file(\"_grad_2.bin\");\n\tfill_signed_distance_field(_3, sdisf, host_data);\n}\n\n}// namespace mn\n\n#endif" }, { "path": "Projects/MGSP/constitutive_models.cuh", "content": "#ifndef CONSTITUTIVE_MODELS_CUH\n#define CONSTITUTIVE_MODELS_CUH\n#include \n#include \n\n#include \n\n//NOLINTNEXTLINE(cppcoreguidelines-macro-usage) Macro usage necessary here for preprocessor if\n#define USE_JOSH_FRACTURE_PAPER 1//Selects which solve is used\n\nnamespace mn {\n\n//TODO: But maybe use names instead for better understanding\n//NOLINTBEGIN(readability-magic-numbers, readability-identifier-naming) Magic numbers are formula specific; Common naming for this physical formulas\ntemplate\n__forceinline__ __device__ void compute_stress_fixed_corotated(T volume, T mu, T lambda, const vec& F, vec& PF) {\n\tstd::array U = {};\n\tstd::array S = {};\n\tstd::array V = {};\n\tmath::svd(F[0], F[3], F[6], F[1], F[4], F[7], F[2], F[5], F[8], U[0], U[3], U[6], U[1], U[4], U[7], U[2], U[5], U[8], S[0], S[1], S[2], V[0], V[3], V[6], V[1], V[4], V[7], V[2], V[5], V[8]);\n\tT J\t\t\t\t= S[0] * S[1] * S[2];\n\tT scaled_mu\t\t= 2.0f * mu;\n\tT scaled_lambda = lambda * (J - 10.f);\n\tvec P_hat;\n\tP_hat[0] = scaled_mu * (S[0] - 1.f) + scaled_lambda * (S[1] * S[2]);\n\tP_hat[1] = scaled_mu * (S[1] - 1.f) + scaled_lambda * (S[0] * S[2]);\n\tP_hat[2] = scaled_mu * (S[2] - 1.f) + scaled_lambda * (S[0] * S[1]);\n\n\tvec P;\n\tP[0] = P_hat[0] * U[0] * V[0] + P_hat[1] * U[3] * V[3] + P_hat[2] * U[6] * V[6];\n\tP[1] = P_hat[0] * U[1] * V[0] + P_hat[1] * U[4] * V[3] + P_hat[2] * U[7] * V[6];\n\tP[2] = P_hat[0] * U[2] * V[0] + P_hat[1] * U[5] * V[3] + P_hat[2] * U[8] * V[6];\n\tP[3] = P_hat[0] * U[0] * V[1] + P_hat[1] * U[3] * V[4] + P_hat[2] * U[6] * V[7];\n\tP[4] = P_hat[0] * U[1] * V[1] + P_hat[1] * U[4] * V[4] + P_hat[2] * U[7] * V[7];\n\tP[5] = P_hat[0] * U[2] * V[1] + P_hat[1] * U[5] * V[4] + P_hat[2] * U[8] * V[7];\n\tP[6] = P_hat[0] * U[0] * V[2] + P_hat[1] * U[3] * V[5] + P_hat[2] * U[6] * V[8];\n\tP[7] = P_hat[0] * U[1] * V[2] + P_hat[1] * U[4] * V[5] + P_hat[2] * U[7] * V[8];\n\tP[8] = P_hat[0] * U[2] * V[2] + P_hat[1] * U[5] * V[5] + P_hat[2] * U[8] * V[8];\n\n\t/// PF'\n\tPF[0] = (P[0] * F[0] + P[3] * F[3] + P[6] * F[6]) * volume;\n\tPF[1] = (P[1] * F[0] + P[4] * F[3] + P[7] * F[6]) * volume;\n\tPF[2] = (P[2] * F[0] + P[5] * F[3] + P[8] * F[6]) * volume;\n\tPF[3] = (P[0] * F[1] + P[3] * F[4] + P[6] * F[7]) * volume;\n\tPF[4] = (P[1] * F[1] + P[4] * F[4] + P[7] * F[7]) * volume;\n\tPF[5] = (P[2] * F[1] + P[5] * F[4] + P[8] * F[7]) * volume;\n\tPF[6] = (P[0] * F[2] + P[3] * F[5] + P[6] * F[8]) * volume;\n\tPF[7] = (P[1] * F[2] + P[4] * F[5] + P[7] * F[8]) * volume;\n\tPF[8] = (P[2] * F[2] + P[5] * F[5] + P[8] * F[8]) * volume;\n}\n//NOLINTEND(readability-magic-numbers, readability-identifier-naming)\n\n//TODO: But maybe use names instead for better understanding\n//NOLINTBEGIN(readability-magic-numbers, readability-identifier-naming) Magic numbers are formula specific; Common naming for this physical formulas\ntemplate\n__forceinline__ __device__ void compute_stress_nacc(T volume, T mu, T lambda, T bm, T xi, T beta, T msqr, bool hardening_on, T& log_jp, vec& F, vec& PF) {\n\t(void) lambda;\n\n\tstd::array U = {};\n\tstd::array S = {};\n\tstd::array V = {};\n\tmath::svd(F[0], F[3], F[6], F[1], F[4], F[7], F[2], F[5], F[8], U[0], U[3], U[6], U[1], U[4], U[7], U[2], U[5], U[8], S[0], S[1], S[2], V[0], V[3], V[6], V[1], V[4], V[7], V[2], V[5], V[8]);\n\tT p0\t= bm * (static_cast(0.00001) + sinh(xi * (-log_jp > 0 ? -log_jp : 0)));\n\tT p_min = -beta * p0;\n\n\tT Je_trial = S[0] * S[1] * S[2];\n\n\t///< 0). calculate YS\n\tstd::array B_hat_trial = {S[0] * S[0], S[1] * S[1], S[2] * S[2]};\n\tT trace_B_hat_trial_divdim\t = (B_hat_trial[0] + B_hat_trial[1] + B_hat_trial[2]) / 3.f;\n\tT J_power_neg_2_d_mulmu\t\t = mu * powf(Je_trial, -2.f / 3.f);///< J^(-2/dim) * mu\n\tstd::array s_hat_trial = {J_power_neg_2_d_mulmu * (B_hat_trial[0] - trace_B_hat_trial_divdim), J_power_neg_2_d_mulmu * (B_hat_trial[1] - trace_B_hat_trial_divdim), J_power_neg_2_d_mulmu * (B_hat_trial[2] - trace_B_hat_trial_divdim)};\n\tT psi_kappa_partial_J\t\t = bm * 0.5f * (Je_trial - 1.f / Je_trial);\n\tT p_trial\t\t\t\t\t = -psi_kappa_partial_J * Je_trial;\n\n\tT y_s_half_coeff\t = 3.f / 2.f * (1 + 2.f * beta);///< a\n\tT y_p_half\t\t\t = (msqr * (p_trial - p_min) * (p_trial - p0));\n\tT s_hat_trial_sqrnorm = s_hat_trial[0] * s_hat_trial[0] + s_hat_trial[1] * s_hat_trial[1] + s_hat_trial[2] * s_hat_trial[2];\n\tT y\t\t\t\t\t = (y_s_half_coeff * s_hat_trial_sqrnorm) + y_p_half;\n\n\t//< 1). update strain and hardening alpha(in log_jp)\n\n\t///< case 1, project to max tip of YS\n\tif(p_trial > p0) {\n\t\tT Je_new = sqrtf(-2.f * p0 / bm + 1.f);\n\t\tS[0] = S[1] = S[2]\t = powf(Je_new, 1.f / 3.f);\n\t\tstd::array New_F = {};\n\t\tmatmul_mat_diag_mat_t_3d(New_F, U, S, V);\n#pragma unroll 9\n\t\tfor(int i = 0; i < 9; i++) {\n\t\t\tF[i] = New_F[i];\n\t\t}\n\t\tif(hardening_on) {\n\t\t\tlog_jp += logf(Je_trial / Je_new);\n\t\t}\n\t}///< case 1 -- end\n\n\t/// case 2, project to min tip of YS\n\telse if(p_trial < p_min) {\n\t\tT Je_new = sqrtf(-2.f * p_min / bm + 1.f);\n\t\tS[0] = S[1] = S[2]\t = powf(Je_new, 1.f / 3.f);\n\t\tstd::array New_F = {};\n\t\tmatmul_mat_diag_mat_t_3d(New_F, U, S, V);\n#pragma unroll 9\n\t\tfor(int i = 0; i < 9; i++) {\n\t\t\tF[i] = New_F[i];\n\t\t}\n\t\tif(hardening_on) {\n\t\t\tlog_jp += logf(Je_trial / Je_new);\n\t\t}\n\t}///< case 2 -- end\n\n\t/// case 3, keep or project to YS by hardening\n\telse {\n\t\t///< outside YS\n\t\tif(y >= 1e-4) {\n\t\t\t////< yield surface projection\n\t\t\tT B_s_coeff = powf(Je_trial, 2.f / 3.f) / mu * sqrtf(-y_p_half / y_s_half_coeff) / sqrtf(s_hat_trial_sqrnorm);\n#pragma unroll 3\n\t\t\tfor(int i = 0; i < 3; i++) {\n\t\t\t\tS[i] = sqrtf(s_hat_trial[i] * B_s_coeff + trace_B_hat_trial_divdim);\n\t\t\t}\n\t\t\tstd::array New_F = {};\n\t\t\tmatmul_mat_diag_mat_t_3d(New_F, U, S, V);\n#pragma unroll 9\n\t\t\tfor(int i = 0; i < 9; i++) {\n\t\t\t\tF[i] = New_F[i];\n\t\t\t}\n\n\t\t\t////< hardening\n\t\t\tif(hardening_on && p0 > 1e-4 && p_trial < p0 - 1e-4 && p_trial > 1e-4 + p_min) {\n\t\t\t\tT p_center = (static_cast(1.0) - beta) * p0 / 2;\n#if USE_JOSH_FRACTURE_PAPER/// solve in 19 Josh Fracture paper\n\t\t\t\tT q_trial\t\t\t\t = sqrtf(3.f / 2.f * s_hat_trial_sqrnorm);\n\t\t\t\tstd::array direction = {p_center - p_trial, -q_trial};\n\t\t\t\tT direction_norm\t\t = sqrtf(direction[0] * direction[0] + direction[1] * direction[1]);\n\t\t\t\tdirection[0] /= direction_norm;\n\t\t\t\tdirection[1] /= direction_norm;\n\n\t\t\t\tT C = msqr * (p_center - p_min) * (p_center - p0);\n\t\t\t\tT B = msqr * direction[0] * (2 * p_center - p0 - p_min);\n\t\t\t\tT A = msqr * direction[0] * direction[0] + (1 + 2 * beta) * direction[1] * direction[1];\n\n\t\t\t\tT l1 = (-B + sqrtf(B * B - 4 * A * C)) / (2 * A);\n\t\t\t\tT l2 = (-B - sqrtf(B * B - 4 * A * C)) / (2 * A);\n\n\t\t\t\tT p1 = p_center + l1 * direction[0];\n\t\t\t\tT p2 = p_center + l2 * direction[0];\n#else/// solve in ziran - Compare_With_Physbam\n\t\t\t\tT aa = msqr * powf(p_trial - p_center, 2) / (y_s_half_coeff * s_hat_trial_sqrnorm);\n\t\t\t\tT dd = 1 + aa;\n\t\t\t\tT ff = aa * beta * p0 - aa * p0 - 2 * p_center;\n\t\t\t\tT gg = (p_center * p_center) - aa * beta * (p0 * p0);\n\t\t\t\tT zz = sqrtf(fabsf(ff * ff - 4 * dd * gg));\n\t\t\t\tT p1 = (-ff + zz) / (2 * dd);\n\t\t\t\tT p2 = (-ff - zz) / (2 * dd);\n#endif\n\n\t\t\t\tT p_fake\t = (p_trial - p_center) * (p1 - p_center) > 0 ? p1 : p2;\n\t\t\t\tT tmp_Je_sqr = (-2 * p_fake / bm + 1);\n\t\t\t\tT Je_new_fake = sqrtf(tmp_Je_sqr > 0 ? tmp_Je_sqr : -tmp_Je_sqr);\n\t\t\t\tif(Je_new_fake > 1e-4) {\n\t\t\t\t\tlog_jp += logf(Je_trial / Je_new_fake);\n\t\t\t\t}\n\t\t\t}\n\t\t}///< outside YS -- end\n\t}\t ///< case 3 --end\n\n\t//< 2). elasticity\n\t///< known: F(renewed), U, V, S(renewed)\n\t///< unknown: J, dev(FF^T)\n\tT J\t\t\t\t\t = S[0] * S[1] * S[2];\n\tstd::array b_dev = {};\n\tstd::array b\t = {};\n\tmatrix_matrix_tranpose_multiplication_3d(F.data_arr(), b);\n\tmatrix_deviatoric_3d(b, b_dev);\n\n\t///< |f| = P * F^T * Volume\n\tT dev_b_coeff = mu * powf(J, -2.f / 3.f);\n\tT i_coeff\t = bm * .5f * (J * J - 1.f);\n\tPF[0]\t\t = (dev_b_coeff * b_dev[0] + i_coeff) * volume;\n\tPF[1]\t\t = (dev_b_coeff * b_dev[1]) * volume;\n\tPF[2]\t\t = (dev_b_coeff * b_dev[2]) * volume;\n\tPF[3]\t\t = (dev_b_coeff * b_dev[3]) * volume;\n\tPF[4]\t\t = (dev_b_coeff * b_dev[4] + i_coeff) * volume;\n\tPF[5]\t\t = (dev_b_coeff * b_dev[5]) * volume;\n\tPF[6]\t\t = (dev_b_coeff * b_dev[6]) * volume;\n\tPF[7]\t\t = (dev_b_coeff * b_dev[7]) * volume;\n\tPF[8]\t\t = (dev_b_coeff * b_dev[8] + i_coeff) * volume;\n}\n//NOLINTEND(readability-magic-numbers, readability-identifier-naming)\n\n//TODO: But maybe use names instead for better understanding\n//NOLINTBEGIN(readability-magic-numbers, readability-identifier-naming) Magic numbers are formula specific; Common naming for this physical formulas\ntemplate\n__forceinline__ __device__ void compute_stress_sand(T volume, T mu, T lambda, T cohesion, T beta, T yield_surface, bool vol_correction, T& log_jp, vec& F, vec& PF) {\n\tstd::array U = {};\n\tstd::array S = {};\n\tstd::array V = {};\n\tmath::svd(F[0], F[3], F[6], F[1], F[4], F[7], F[2], F[5], F[8], U[0], U[3], U[6], U[1], U[4], U[7], U[2], U[5], U[8], S[0], S[1], S[2], V[0], V[3], V[6], V[1], V[4], V[7], V[2], V[5], V[8]);\n\tT scaled_mu = static_cast(2.0) * mu;\n\n\tstd::array epsilon = {};\n\tstd::array New_S\t = {};///< helper\n\tstd::array New_F\t = {};\n\n#pragma unroll 3\n\tfor(int i = 0; i < 3; i++) {\n\t\tT abs_S\t = S[i] > 0 ? S[i] : -S[i];\n\t\tabs_S\t = abs_S > static_cast(1e-4) ? abs_S : static_cast(1e-4);\n\t\tepsilon[i] = logf(abs_S) - cohesion;\n\t}\n\tT sum_epsilon\t= epsilon[0] + epsilon[1] + epsilon[2];\n\tT trace_epsilon = sum_epsilon + log_jp;\n\n\tstd::array epsilon_hat = {};\n#pragma unroll 3\n\tfor(int i = 0; i < 3; i++) {\n\t\tepsilon_hat[i] = epsilon[i] - (trace_epsilon / static_cast(3.0));\n\t}\n\n\tT epsilon_hat_norm = sqrtf(epsilon_hat[0] * epsilon_hat[0] + epsilon_hat[1] * epsilon_hat[1] + epsilon_hat[2] * epsilon_hat[2]);\n\n\t/* Calculate Plasticiy */\n\tif(trace_epsilon >= static_cast(0.0)) {///< case II: project to the cone tip\n\t\tNew_S[0] = New_S[1] = New_S[2] = expf(cohesion);\n\t\tmatmul_mat_diag_mat_t_3d(New_F, U, New_S, V);// new F_e\n\t\t\t\t\t\t\t\t\t\t\t\t\t /* Update F */\n#pragma unroll 9\n\t\tfor(int i = 0; i < 9; i++) {\n\t\t\tF[i] = New_F[i];\n\t\t}\n\t\tif(vol_correction) {\n\t\t\tlog_jp = beta * sum_epsilon + log_jp;\n\t\t}\n\t} else if(mu != 0) {\n\t\tlog_jp\t\t\t = 0;\n\t\tT delta_gamma\t = epsilon_hat_norm + (static_cast(3.0) * lambda + scaled_mu) / scaled_mu * trace_epsilon * yield_surface;\n\t\tstd::array H = {};\n\t\tif(delta_gamma <= 0) {///< case I: inside the yield surface cone\n#pragma unroll 3\n\t\t\tfor(int i = 0; i < 3; i++) {\n\t\t\t\tH[i] = epsilon[i] + cohesion;\n\t\t\t}\n\t\t} else {///< case III: project to the cone surface\n#pragma unroll 3\n\t\t\tfor(int i = 0; i < 3; i++) {\n\t\t\t\tH[i] = epsilon[i] - (delta_gamma / epsilon_hat_norm) * epsilon_hat[i] + cohesion;\n\t\t\t}\n\t\t}\n#pragma unroll 3\n\t\tfor(int i = 0; i < 3; i++) {\n\t\t\tNew_S[i] = expf(H[i]);\n\t\t}\n\t\tmatmul_mat_diag_mat_t_3d(New_F, U, New_S, V);// new F_e\n\t\t\t\t\t\t\t\t\t\t\t\t\t /* Update F */\n#pragma unroll 9\n\t\tfor(int i = 0; i < 9; i++) {\n\t\t\tF[i] = New_F[i];\n\t\t}\n\t} else {\n\t\t//TODO: What to do here? Just don't change values?\n\t}\n\n\t/* Elasticity -- Calculate Coefficient */\n\tstd::array New_S_log = {logf(New_S[0]), logf(New_S[1]), logf(New_S[2])};\n\tstd::array P_hat\t = {};\n\n\t// T S_inverse[3] = {1.f/S[0], 1.f/S[1], 1.f/S[2]}; // TO CHECK\n\t// T S_inverse[3] = {1.f / New_S[0], 1.f / New_S[1], 1.f / New_S[2]}; // TO\n\t// CHECK\n\tT trace_log_S = New_S_log[0] + New_S_log[1] + New_S_log[2];\n#pragma unroll 3\n\tfor(int i = 0; i < 3; i++) {\n\t\tP_hat[i] = (scaled_mu * New_S_log[i] + lambda * trace_log_S) / New_S[i];\n\t}\n\n\tstd::array P = {};\n\tmatmul_mat_diag_mat_t_3d(P, U, P_hat, V);\n\t///< |f| = P * F^T * Volume\n\tPF[0] = (P[0] * F[0] + P[3] * F[3] + P[6] * F[6]) * volume;\n\tPF[1] = (P[1] * F[0] + P[4] * F[3] + P[7] * F[6]) * volume;\n\tPF[2] = (P[2] * F[0] + P[5] * F[3] + P[8] * F[6]) * volume;\n\tPF[3] = (P[0] * F[1] + P[3] * F[4] + P[6] * F[7]) * volume;\n\tPF[4] = (P[1] * F[1] + P[4] * F[4] + P[7] * F[7]) * volume;\n\tPF[5] = (P[2] * F[1] + P[5] * F[4] + P[8] * F[7]) * volume;\n\tPF[6] = (P[0] * F[2] + P[3] * F[5] + P[6] * F[8]) * volume;\n\tPF[7] = (P[1] * F[2] + P[4] * F[5] + P[7] * F[8]) * volume;\n\tPF[8] = (P[2] * F[2] + P[5] * F[5] + P[8] * F[8]) * volume;\n}\n//NOLINTEND(readability-magic-numbers, readability-identifier-naming)\n\n}// namespace mn\n\n#endif" }, { "path": "Projects/MGSP/grid_buffer.cuh", "content": "#ifndef GRID_BUFFER_CUH\n#define GRID_BUFFER_CUH\n#include \n\n#include \"mgmpm_kernels.cuh\"\n#include \"settings.h\"\n\nnamespace mn {\nusing namespace placeholder;//NOLINT(google-build-using-namespace) Allow placeholders to be included generally for simplification\n\n//NOLINTBEGIN(cppcoreguidelines-avoid-non-const-global-variables, readability-identifier-naming) Check is buggy and reporst variable errors fro template arguments\nusing BlockDomain\t = CompactDomain;\nusing GridDomain\t = CompactDomain;\nusing GridBufferDomain = CompactDomain;\n\nusing grid_block_ = Structural, BlockDomain, attrib_layout::SOA, f32_, f32_, f32_, f32_>;\nusing grid_\t\t = Structural, GridDomain, attrib_layout::AOS, grid_block_>;\nusing grid_buffer_ = Structural, GridBufferDomain, attrib_layout::AOS, grid_block_>;\n//NOLINTEND(cppcoreguidelines-avoid-non-const-global-variables, readability-identifier-naming)\n\nstruct GridBuffer : Instance {\n\tusing base_t = Instance;\n\n\ttemplate\n\texplicit GridBuffer(Allocator allocator)\n\t\t: base_t {spawn(allocator)} {}\n\ttemplate\n\tvoid check_capacity(Allocator allocator, std::size_t capacity) {\n\t\tif(capacity > this->capacity) {\n\t\t\tthis->resize(allocator, capacity);\n\t\t}\n\t}\n\ttemplate\n\tvoid reset(int block_count, CudaContext& cu_dev) {\n\t\t//check_cuda_errors(cudaMemsetAsync((void *)&this->val_1d(_0, 0), 0, grid_block_::size * block_count, cu_dev.stream_compute()));\n\t\tcu_dev.compute_launch({block_count, config::G_BLOCKVOLUME}, clear_grid, *this);\n\t}\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Projects/MGSP/halo_buffer.cuh", "content": "#ifndef HALO_BUFFER_CUH\n#define HALO_BUFFER_CUH\n#include \n\n#include \"grid_buffer.cuh\"\n#include \"particle_buffer.cuh\"\n#include \"settings.h\"\n//#include \n\nnamespace mn {\n\nusing HaloGridBlocksDomain = CompactDomain;\nusing halo_grid_blocks_\t = Structural, HaloGridBlocksDomain, attrib_layout::SOA, grid_block_>;\n\nusing grid_block_ = Structural, BlockDomain, attrib_layout::SOA, f32_, f32_, f32_, f32_>;\n\n/// halo grid block\nstruct HaloGridBlocks {\n\tstruct HaloBuffer {\n\t\tInstance grid;\n\t\tivec3* blockids;\n\t};\n\n\tint num_targets;\n\tuint32_t* counts;\n\tstd::vector h_counts;\n\tstd::vector buffers;\n\n\texplicit HaloGridBlocks(int num_neighbors)\n\t\t: num_targets {num_neighbors}\n\t\t, counts(nullptr)\n\t\t, h_counts(num_neighbors, 0) {\n\t\tcheck_cuda_errors(cudaMalloc(&counts, sizeof(uint32_t) * num_targets));\n\t\tbuffers.resize(num_targets);\n\t}\n\ttemplate\n\tvoid init_blocks(Allocator allocator, uint32_t block_count) {\n\t\tfor(int did = 0; did < num_targets; ++did) {\n\t\t\tbuffers[did].blockids = static_cast(allocator.allocate(sizeof(ivec3) * block_count));\n\t\t}\n\t}\n\ttemplate\n\tvoid init_buffer(Allocator allocator, std::vector counts) {\n\t\tfor(int did = 0; did < num_targets; ++did) {\n\t\t\tbuffers[did].grid.allocate_handle(allocator, counts[did]);\n\t\t}\n\t}\n\tvoid reset_counts(cudaStream_t stream) {\n\t\tcheck_cuda_errors(cudaMemsetAsync(counts, 0, sizeof(uint32_t) * num_targets, stream));\n\t}\n\tvoid retrieve_counts(cudaStream_t stream) {\n\t\tcheck_cuda_errors(cudaMemcpyAsync(h_counts.data(), counts, sizeof(uint32_t) * num_targets, cudaMemcpyDefault, stream));\n\t}\n\tvoid send(HaloGridBlocks& other, int src, int dst, cudaStream_t stream) {\n\t\tauto count = other.h_counts[src] = h_counts[dst];\n\t\t//check_cuda_errors(cudaMemcpyAsync( &other.buffers[src].val(_1, 0), &buffers[dst].val(_1, 0), sizeof(ivec3) * count, cudaMemcpyDefault, stream));\n\t\tcheck_cuda_errors(cudaMemcpyAsync(other.buffers[src].blockids, buffers[dst].blockids, sizeof(ivec3) * count, cudaMemcpyDefault, stream));\n\t\t//check_cuda_errors(cudaMemcpyAsync(&other.buffers[src].grid.ch(_0, 0).val_1d(_0, 0), &buffers[dst].grid.ch(_0, 0).val_1d(_0, 0), grid_block_::size * count, cudaMemcpyDefault, stream));\n\t\tcheck_cuda_errors(cudaMemcpyPeerAsync(&other.buffers[src].grid.ch(_0, 0).val_1d(_0, 0), dst, &buffers[dst].grid.ch(_0, 0).val_1d(_0, 0), src, grid_block_::size * count, stream));\n\t\t// printf(\"sending from %d to %d at %llu\\n\", src, dst,\n\t\t// (unsigned long long)&other.buffers[src].grid.ch(_0, 0).val_1d(_0,\n\t\t// 0));\n\t}\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Projects/MGSP/halo_kernels.cuh", "content": "#ifndef HALO_KERNELS_CUH\n#define HALO_KERNELS_CUH\n\n#include \n\n#include \n#include \n\n#include \"constitutive_models.cuh\"\n#include \"particle_buffer.cuh\"\n#include \"settings.h\"\n#include \"utility_funcs.hpp\"\n\nnamespace mn {\n\nusing namespace placeholder;//NOLINT(google-build-using-namespace) Allow placeholders to be included generally for simplification\n\n//TODO: Make magic numbers to constants where suitable\n//TODO: Ensure call dimensions and such are small enough to allow narrowing conversations. Or directly use unsigned where possible\n//NOLINTBEGIN(cppcoreguidelines-pro-bounds-pointer-arithmetic, readability-magic-numbers, misc-definitions-in-headers) CUDA does not yet support std::span; Cannot declare __global__ functions inline\ntemplate\n__global__ void mark_overlapping_blocks(uint32_t block_count, int otherdid, const ivec3* __restrict__ incoming_block_ids, Partition partition, uint32_t* count, HaloGridBlocks halo_grid_blocks) {\n\tuint32_t inc_blockno = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(inc_blockno >= block_count) {\n\t\treturn;\n\t}\n\tauto inc_blockid = incoming_block_ids[inc_blockno];\n\tauto blockno\t = partition.query(inc_blockid);\n\tif(blockno >= 0) {\n\t\tatomicOr(partition.overlap_marks + blockno, 1 << otherdid);\n\t\tauto halono = atomicAdd(count, 1);\n\t\t// halo_grid_blocks.val(_1, halono) = inc_blockid;\n\t\thalo_grid_blocks.blockids[halono] = inc_blockid;\n\t}\n}\n\ntemplate\n__global__ void collect_blockids_for_halo_reduction(uint32_t particle_block_count, int did, Partition partition) {\n\t(void) did;\n\n\tstd::size_t blockno = static_cast(blockIdx.x) * blockDim.x + threadIdx.x;\n\tif(blockno >= particle_block_count) {\n\t\treturn;\n\t}\n\tauto blockid\t\t\t\t = partition.active_keys[blockno];\n\tpartition.halo_marks[blockno] = 0;\n\tfor(char i = 0; i < 2; ++i) {\n\t\tfor(char j = 0; j < 2; ++j) {\n\t\t\tfor(char k = 0; k < 2; ++k) {\n\t\t\t\tivec3 neighborid {blockid[0] + i, blockid[1] + j, blockid[2] + k};\n\t\t\t\tint neighborno = partition.query(neighborid);\n\t\t\t\t// if (partition.overlap_marks[neighborno] ^ ((HaloIndex)1 << did)) {\n\t\t\t\tif(partition.overlap_marks[neighborno]) {\n\t\t\t\t\tpartition.halo_marks[blockno] = 1;\n\t\t\t\t\tauto halono\t\t\t\t\t = atomicAdd(partition.halo_count, 1);\n\t\t\t\t\tpartition.halo_blocks[halono] = blockid;\n\t\t\t\t\treturn;\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\ntemplate\n__global__ void collect_grid_blocks(Grid grid, Partition partition, HaloGridBlocks halo_grid_blocks) {\n\tuint32_t halo_blockno = blockIdx.x;\n\t// auto halo_blockid = halo_grid_blocks.grid.val(_1, halo_blockno);\n\tauto halo_blockid = halo_grid_blocks.blockids[halo_blockno];\n\n\tauto blockno\t\t= partition.query(halo_blockid);\n\tauto halo_gridblock = halo_grid_blocks.grid.ch(_0, halo_blockno);\n\tauto gridblock\t\t= grid.ch(_0, blockno);\n\n\tfor(int cell_id_in_block = static_cast(threadIdx.x); cell_id_in_block < config::G_BLOCKVOLUME; cell_id_in_block += static_cast(blockDim.x)) {\n\t\thalo_gridblock.val_1d(_0, cell_id_in_block) = gridblock.val_1d(_0, cell_id_in_block);\n\t\thalo_gridblock.val_1d(_1, cell_id_in_block) = gridblock.val_1d(_1, cell_id_in_block);\n\t\thalo_gridblock.val_1d(_2, cell_id_in_block) = gridblock.val_1d(_2, cell_id_in_block);\n\t\thalo_gridblock.val_1d(_3, cell_id_in_block) = gridblock.val_1d(_3, cell_id_in_block);\n\t}\n}\n\ntemplate\n__global__ void reduce_grid_blocks(Grid grid, Partition partition, HaloGridBlocks halo_grid_blocks) {\n\tuint32_t halo_blockno = blockIdx.x;\n\t// auto halo_blockid = halo_grid_blocks.grid.val(_1, halo_blockno);\n\tauto halo_blockid\t= halo_grid_blocks.blockids[halo_blockno];\n\tauto blockno\t\t= partition.query(halo_blockid);\n\tauto halo_gridblock = halo_grid_blocks.grid.ch(_0, halo_blockno);\n\tauto gridblock\t\t= grid.ch(_0, blockno);\n\n\tfor(int cell_id_in_block = static_cast(threadIdx.x); cell_id_in_block < config::G_BLOCKVOLUME; cell_id_in_block += static_cast(blockDim.x)) {\n\t\tatomicAdd(&gridblock.val_1d(_0, cell_id_in_block), halo_gridblock.val_1d(_0, cell_id_in_block));\n\t\tatomicAdd(&gridblock.val_1d(_1, cell_id_in_block), halo_gridblock.val_1d(_1, cell_id_in_block));\n\t\tatomicAdd(&gridblock.val_1d(_2, cell_id_in_block), halo_gridblock.val_1d(_2, cell_id_in_block));\n\t\tatomicAdd(&gridblock.val_1d(_3, cell_id_in_block), halo_gridblock.val_1d(_3, cell_id_in_block));\n\t}\n}\n\ntemplate\n__global__ void mark_migration_grid_blocks(uint32_t block_count, Domain const domain, Partition const partition, uint32_t* count, HaloParticleBlocks halo_particle_blocks, int const* active_grid_block_marks) {\n\tuint32_t blockno = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(blockno >= block_count) {\n\t\treturn;\n\t}\n\tif(active_grid_block_marks[blockno]) {\n\t\tauto blockid = partition.active_keys[blockno];\n\t\tif(domain.within(blockid, ivec3 {0, 0, 0}, ivec3 {1, 1, 1})) {\n\t\t\t// halo_particle_blocks._binpbs[halono] = 0;\n\t\t\tauto halono\t\t\t\t\t\t\t\t= atomicAdd(count, 1);\n\t\t\thalo_particle_blocks._gblockids[halono] = blockid;\n\t\t}\n\t}\n}\n\ntemplate\n__global__ void collect_migration_grid_blocks(Grid grid, Partition partition, HaloGridBlocks halo_grid_blocks) {\n\tuint32_t halo_blockno = blockIdx.x;\n\tauto halo_blockid\t = halo_grid_blocks._gblockids[halo_blockno];\n\tauto halo_gridblock\t = halo_grid_blocks._grid.ch(_0, halo_blockno);\n\n\tauto blockno = partition.query(halo_blockid);\n\tauto gridblock = grid.ch(_0, blockno);\n\n\tfor(int cell_id_in_block = static_cast(threadIdx.x); cell_id_in_block < config::G_BLOCKVOLUME; cell_id_in_block += static_cast(blockDim.x)) {\n\t\thalo_gridblock.val_1d(_0, cell_id_in_block) = gridblock.val_1d(_0, cell_id_in_block);\n\t\thalo_gridblock.val_1d(_1, cell_id_in_block) = gridblock.val_1d(_1, cell_id_in_block);\n\t\thalo_gridblock.val_1d(_2, cell_id_in_block) = gridblock.val_1d(_2, cell_id_in_block);\n\t\thalo_gridblock.val_1d(_3, cell_id_in_block) = gridblock.val_1d(_3, cell_id_in_block);\n\t}\n}\n//NOLINTEND(cppcoreguidelines-pro-bounds-pointer-arithmetic, readability-magic-numbers, misc-definitions-in-headers)\n\n}// namespace mn\n\n#endif" }, { "path": "Projects/MGSP/hash_table.cuh", "content": "#ifndef HASH_TABLE_CUH\n#define HASH_TABLE_CUH\n\n#include \n\n#include \"mgmpm_kernels.cuh\"\n#include \"settings.h\"\n\n//NOLINTNEXTLINE(cppcoreguidelines-macro-usage) Macro usage necessary here for preprocessor if\n#define PRINT_NEGATIVE_BLOGNOS 1\n\nnamespace mn {\n\ntemplate\nstruct HaloPartition {\n\ttemplate\n\tHaloPartition(Allocator allocator, int max_block_count) {\n\t\t(void) allocator;\n\t\t(void) max_block_count;\n\t}\n\n\ttemplate\n\tvoid resize_partition(Allocator allocator, std::size_t prev_capacity, std::size_t capacity) {}\n\tvoid copy_to(HaloPartition& other, std::size_t block_count, cudaStream_t stream) {}\n};\ntemplate<>\nstruct HaloPartition<1> {\n\tint* halo_count;\n\tint h_count;\n\tchar* halo_marks;///< halo particle blocks\n\tint* overlap_marks;\n\tivec3* halo_blocks;\n\n\ttemplate\n\tHaloPartition(Allocator allocator, int max_block_count)\n\t\t: h_count(0) {\n\t\thalo_count\t = static_cast(allocator.allocate(sizeof(char) * max_block_count));\n\t\thalo_marks\t = static_cast(allocator.allocate(sizeof(char) * max_block_count));\n\t\toverlap_marks = static_cast(allocator.allocate(sizeof(int) * max_block_count));\n\t\thalo_blocks\t = static_cast(allocator.allocate(sizeof(ivec3) * max_block_count));\n\t}\n\n\tvoid copy_to(HaloPartition& other, std::size_t block_count, cudaStream_t stream) const {\n\t\tother.h_count = h_count;\n\t\tcheck_cuda_errors(cudaMemcpyAsync(other.halo_marks, halo_marks, sizeof(char) * block_count, cudaMemcpyDefault, stream));\n\t\tcheck_cuda_errors(cudaMemcpyAsync(other.overlap_marks, overlap_marks, sizeof(int) * block_count, cudaMemcpyDefault, stream));\n\t\tcheck_cuda_errors(cudaMemcpyAsync(other.halo_blocks, halo_blocks, sizeof(ivec3) * block_count, cudaMemcpyDefault, stream));\n\t}\n\n\ttemplate\n\tvoid resize_partition(Allocator allocator, std::size_t prev_capacity, std::size_t capacity) {\n\t\tallocator.deallocate(halo_marks, sizeof(char) * prev_capacity);\n\t\tallocator.deallocate(overlap_marks, sizeof(int) * prev_capacity);\n\t\tallocator.deallocate(halo_blocks, sizeof(ivec3) * prev_capacity);\n\t\thalo_marks\t = static_cast(allocator.allocate(sizeof(char) * capacity));\n\t\toverlap_marks = static_cast(allocator.allocate(sizeof(int) * capacity));\n\t\thalo_blocks\t = static_cast(allocator.allocate(sizeof(ivec3) * capacity));\n\t}\n\n\tvoid reset_halo_count(cudaStream_t stream) const {\n\t\tcheck_cuda_errors(cudaMemsetAsync(halo_count, 0, sizeof(int), stream));\n\t}\n\n\tvoid reset_overlap_marks(uint32_t neighbor_block_count, cudaStream_t stream) const {\n\t\tcheck_cuda_errors(cudaMemsetAsync(overlap_marks, 0, sizeof(int) * neighbor_block_count, stream));\n\t}\n\n\tvoid retrieve_halo_count(cudaStream_t stream) {\n\t\tcheck_cuda_errors(cudaMemcpyAsync(&h_count, halo_count, sizeof(int), cudaMemcpyDefault, stream));\n\t}\n};\n\n//NOLINTBEGIN(cppcoreguidelines-avoid-non-const-global-variables, readability-identifier-naming) Check is buggy and reporst variable errors fro template arguments\nusing block_partition_ = Structural, GridDomain, attrib_layout::AOS, empty_>;\n//NOLINTEND(cppcoreguidelines-avoid-non-const-global-variables, readability-identifier-naming)\n\n//NOLINTBEGIN(cppcoreguidelines-pro-bounds-pointer-arithmetic) Using pointer arithmetics cause library and allocators do so.\ntemplate\nstruct Partition\n\t: Instance\n\t, HaloPartition {\n\tusing base_t\t = Instance;\n\tusing halo_base_t = HaloPartition;\n\tusing block_partition_::key_t;\n\tusing block_partition_::value_t;\n\tstatic_assert(sentinel_v == (value_t) (-1), \"sentinel value not full 1s\\n\");\n\n\tint* cell_particle_counts;\n\tint* particle_bucket_sizes;\n\tint* cellbuckets;\n\tint* blockbuckets;\n\tint* bin_offsets;\n\n\ttemplate\n\tPartition(Allocator allocator, int max_block_count)\n\t\t: halo_base_t {allocator, max_block_count} {\n\t\tallocate_table(allocator, max_block_count);\n\t\tcell_particle_counts = static_cast(allocator.allocate(sizeof(int) * max_block_count * config::G_BLOCKVOLUME));\n\t\tparticle_bucket_sizes = static_cast(allocator.allocate(sizeof(int) * max_block_count));\n\t\tcellbuckets\t\t\t = static_cast(allocator.allocate(sizeof(int) * max_block_count * config::G_BLOCKVOLUME * config::G_MAX_PARTICLES_IN_CELL));\n\t\tblockbuckets\t\t = static_cast(allocator.allocate(sizeof(int) * max_block_count * config::G_PARTICLE_NUM_PER_BLOCK));\n\t\tbin_offsets\t\t\t = static_cast(allocator.allocate(sizeof(int) * max_block_count));\n\n\t\t/// init\n\t\treset();\n\t}\n\n\t~Partition() = default;\n\n\tPartition(const Partition& other)\t\t\t\t = default;\n\tPartition(Partition&& other) noexcept\t\t\t = default;\n\tPartition& operator=(const Partition& other)\t = default;\n\tPartition& operator=(Partition&& other) noexcept = default;\n\n\ttemplate\n\tvoid resize_partition(Allocator allocator, std::size_t capacity) {\n\t\thalo_base_t::resize_partition(allocator, this->capacity, capacity);\n\n\t\tallocator.deallocate(cell_particle_counts, sizeof(int) * this->capacity * config::G_BLOCKVOLUME);\n\t\tallocator.deallocate(particle_bucket_sizes, sizeof(int) * this->capacity);\n\t\tallocator.deallocate(cellbuckets, sizeof(int) * this->capacity * config::G_BLOCKVOLUME * config::G_MAX_PARTICLES_IN_CELL);\n\t\tallocator.deallocate(blockbuckets, sizeof(int) * this->capacity * config::G_BLOCKVOLUME);\n\t\tallocator.deallocate(bin_offsets, sizeof(int) * this->capacity);\n\n\t\tcell_particle_counts = static_cast(allocator.allocate(sizeof(int) * capacity * config::G_BLOCKVOLUME));\n\t\tparticle_bucket_sizes = static_cast(allocator.allocate(sizeof(int) * capacity));\n\t\tcellbuckets\t\t\t = static_cast(allocator.allocate(sizeof(int) * capacity * config::G_BLOCKVOLUME * config::G_MAX_PARTICLES_IN_CELL));\n\t\tblockbuckets\t\t = static_cast(allocator.allocate(sizeof(int) * capacity * config::G_PARTICLE_NUM_PER_BLOCK));\n\t\tbin_offsets\t\t\t = static_cast(allocator.allocate(sizeof(int) * capacity));\n\n\t\tresize_table(allocator, capacity);\n\t}\n\n\tvoid reset() {\n\t\tcheck_cuda_errors(cudaMemset(this->Instance::count, 0, sizeof(value_t)));\n\t\tcheck_cuda_errors(cudaMemset(this->index_table, 0xff, sizeof(value_t) * domain::extent));\n\t\tcheck_cuda_errors(cudaMemset(this->cell_particle_counts, 0, sizeof(int) * this->capacity * config::G_BLOCKVOLUME));\n\t}\n\tvoid reset_table(cudaStream_t stream) {\n\t\tcheck_cuda_errors(cudaMemsetAsync(this->index_table, 0xff, sizeof(value_t) * domain::extent, stream));\n\t}\n\ttemplate\n\tvoid build_particle_buckets(CudaContext&& cu_dev, value_t count) {\n\t\tcheck_cuda_errors(cudaMemsetAsync(this->particle_bucket_sizes, 0, sizeof(int) * (count + 1), cu_dev.stream_compute()));\n\t\tcu_dev.compute_launch({count, config::G_BLOCKVOLUME}, cell_bucket_to_block, cell_particle_counts, cellbuckets, particle_bucket_sizes, blockbuckets);\n\t}\n\tvoid copy_to(Partition& other, std::size_t block_count, cudaStream_t stream) {\n\t\thalo_base_t::copy_to(other, block_count, stream);\n\t\tcheck_cuda_errors(cudaMemcpyAsync(other.index_table, this->index_table, sizeof(value_t) * domain::extent, cudaMemcpyDefault, stream));\n\t\tcheck_cuda_errors(cudaMemcpyAsync(other.particle_bucket_sizes, this->particle_bucket_sizes, sizeof(int) * block_count, cudaMemcpyDefault, stream));\n\t\tcheck_cuda_errors(cudaMemcpyAsync(other.bin_offsets, this->bin_offsets, sizeof(int) * block_count, cudaMemcpyDefault, stream));\n\t}\n\t__forceinline__ __device__ value_t insert(key_t key) noexcept {\n\t\tvalue_t tag = atomicCAS(&this->index(key), sentinel_v, 0);\n\t\tif(tag == sentinel_v) {\n\t\t\tvalue_t idx\t\t\t = atomicAdd(this->Instance::count, 1);\n\t\t\tthis->index(key)\t = idx;\n\t\t\tthis->active_keys[idx] = key;///< created a record\n\t\t\treturn idx;\n\t\t}\n\t\treturn -1;\n\t}\n\t__forceinline__ __device__ value_t query(key_t key) const noexcept {\n\t\treturn this->index(key);\n\t}\n\t__forceinline__ __device__ void reinsert(value_t index) {\n\t\tthis->index(this->active_keys[index]) = index;\n\t}\n\t__forceinline__ __device__ void add_advection(key_t cellid, int dirtag, int particle_id_in_block) noexcept {\n\t\tkey_t blockid\t= cellid / config::G_BLOCKSIZE;\n\t\tvalue_t blockno = query(blockid);\n#if PRINT_NEGATIVE_BLOGNOS\n\t\tif(blockno == -1) {\n\t\t\tivec3 offset {};\n\t\t\tdir_components(dirtag, offset);\n\t\t\t//NOLINTNEXTLINE(cppcoreguidelines-pro-type-vararg, readability-magic-numbers) Cuda has no other way to print; Numbers are array indices to be printed\n\t\t\tprintf(\"The hell with this! loc(%d, %d, %d) dir(%d, %d, %d) particle_id_in_block(%d)\\n\", cellid[0], cellid[1], cellid[2], offset[0], offset[1], offset[2], particle_id_in_block);\n\t\t\treturn;\n\t\t}\n#endif\n\t\t//NOLINTNEXTLINE(readability-magic-numbers) Numbers are array indices to be printed\n\t\tvalue_t cellno\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t = ((cellid[0] & config::G_BLOCKMASK) << (config::G_BLOCKBITS << 1)) | ((cellid[1] & config::G_BLOCKMASK) << config::G_BLOCKBITS) | (cellid[2] & config::G_BLOCKMASK);\n\t\tint particle_id_in_cell\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t = atomicAdd(cell_particle_counts + static_cast(blockno) * config::G_BLOCKVOLUME + cellno, 1);\n\t\tcellbuckets[blockno * config::G_PARTICLE_NUM_PER_BLOCK + cellno * config::G_MAX_PARTICLES_IN_CELL + particle_id_in_cell] = (dirtag * config::G_PARTICLE_NUM_PER_BLOCK) | particle_id_in_block;\n\t}\n};\n//NOLINTEND(cppcoreguidelines-pro-bounds-pointer-arithmetic)\n\n}// namespace mn\n\n#endif" }, { "path": "Projects/MGSP/mgmpm_kernels.cuh", "content": "#ifndef MULTI_GMPM_KERNELS_CUH\n#define MULTI_GMPM_KERNELS_CUH\n\n#include \n\n#include \n#include \n\n#include \"boundary_condition.cuh\"\n#include \"constitutive_models.cuh\"\n#include \"particle_buffer.cuh\"\n#include \"settings.h\"\n#include \"utility_funcs.hpp\"\n\nnamespace mn {\nusing namespace placeholder;//NOLINT(google-build-using-namespace) Allow placeholders to be included generally for simplification\n\n//TODO: Make magic numbers to constants where suitable\n//TODO: Ensure call dimensions and such are small enough to allow narrowing conversations. Or directly use unsigned where possible\n//TODO: Maybe use names instead of formula signs for better understanding\n//NOLINTBEGIN(cppcoreguidelines-pro-bounds-pointer-arithmetic, readability-magic-numbers, readability-identifier-naming, misc-definitions-in-headers) CUDA does not yet support std::span; Common names for physical formulas; Cannot declare __global__ functions inline\ntemplate\n__global__ void activate_blocks(uint32_t particle_counts, ParticleArray particle_array, Partition partition) {\n\tuint32_t particle_id = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(particle_id >= particle_counts) {\n\t\treturn;\n\t}\n\tivec3 blockid {static_cast((std::lround(particle_array.val(_0, particle_id) / config::G_DX) - 2) / config::G_BLOCKSIZE), static_cast((std::lround(particle_array.val(_1, particle_id) / config::G_DX) - 2) / config::G_BLOCKSIZE), static_cast((std::lround(particle_array.val(_2, particle_id) / config::G_DX) - 2) / config::G_BLOCKSIZE)};\n\tpartition.insert(blockid);\n}\ntemplate\n__global__ void build_particle_cell_buckets(uint32_t particle_counts, ParticleArray particle_array, Partition partition) {\n\tuint32_t particle_id = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(particle_id >= particle_counts) {\n\t\treturn;\n\t}\n\tivec3 coord {int(std::lround(particle_array.val(_0, particle_id) / config::G_DX) - 2), int(std::lround(particle_array.val(_1, particle_id) / config::G_DX) - 2), int(std::lround(particle_array.val(_2, particle_id) / config::G_DX) - 2)};\n\tint cellno\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t = (coord[0] & config::G_BLOCKMASK) * config::G_BLOCKSIZE * config::G_BLOCKSIZE + (coord[1] & config::G_BLOCKMASK) * config::G_BLOCKSIZE + (coord[2] & config::G_BLOCKMASK);\n\tcoord\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t = coord / static_cast(config::G_BLOCKSIZE);\n\tauto blockno\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t = partition.query(coord);\n\tauto particle_id_in_cell\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t = atomicAdd(partition.cell_particle_counts + blockno * config::G_BLOCKVOLUME + cellno, 1);\n\tpartition.cellbuckets[blockno * config::G_PARTICLE_NUM_PER_BLOCK + cellno * config::G_MAX_PARTICLES_IN_CELL + particle_id_in_cell] = static_cast(particle_id);//NOTE:Explicit narrowing conversation.\n}\n__global__ void cell_bucket_to_block(const int* cell_particle_counts, const int* cellbuckets, int* particle_bucket_sizes, int* buckets) {\n\tconst int cellno\t\t = static_cast(threadIdx.x) & (config::G_BLOCKVOLUME - 1);\n\tconst int particle_counts = cell_particle_counts[blockIdx.x * config::G_BLOCKVOLUME + cellno];\n\tfor(int particle_id_in_cell = 0; particle_id_in_cell < config::G_MAX_PARTICLES_IN_CELL; particle_id_in_cell++) {\n\t\tif(particle_id_in_cell < particle_counts) {\n\t\t\tauto particle_id_in_block\t\t\t\t\t\t\t\t\t\t\t\t\t = atomic_agg_inc(particle_bucket_sizes + blockIdx.x);\n\t\t\tbuckets[blockIdx.x * config::G_PARTICLE_NUM_PER_BLOCK + particle_id_in_block] = cellbuckets[blockIdx.x * config::G_PARTICLE_NUM_PER_BLOCK + cellno * config::G_MAX_PARTICLES_IN_CELL + particle_id_in_cell];\n\t\t}\n\t\t__syncthreads();\n\t}\n}\n__global__ void compute_bin_capacity(uint32_t block_count, int const* particle_bucket_sizes, int* bin_sizes) {\n\tconst uint32_t blockno = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(blockno >= block_count) {\n\t\treturn;\n\t}\n\tbin_sizes[blockno] = (particle_bucket_sizes[blockno] + config::G_BIN_CAPACITY - 1) / config::G_BIN_CAPACITY;\n}\n__global__ void init_adv_bucket(const int* particle_bucket_sizes, int* buckets) {\n\tint particle_counts = particle_bucket_sizes[blockIdx.x];\n\tint* bucket\t\t\t= buckets + static_cast(blockIdx.x) * config::G_PARTICLE_NUM_PER_BLOCK;\n\tfor(int particle_id_in_block = static_cast(threadIdx.x); particle_id_in_block < particle_counts; particle_id_in_block += static_cast(blockDim.x)) {\n\t\tbucket[particle_id_in_block] = (dir_offset(ivec3 {0, 0, 0}) * config::G_PARTICLE_NUM_PER_BLOCK) | particle_id_in_block;\n\t}\n}\ntemplate\n__global__ void clear_grid(Grid grid) {\n\tauto gridblock = grid.ch(_0, blockIdx.x);\n\tfor(int cell_id_in_block = static_cast(threadIdx.x); cell_id_in_block < config::G_BLOCKVOLUME; cell_id_in_block += static_cast(blockDim.x)) {\n\t\tgridblock.val_1d(_0, cell_id_in_block) = 0.f;\n\t\tgridblock.val_1d(_1, cell_id_in_block) = 0.f;\n\t\tgridblock.val_1d(_2, cell_id_in_block) = 0.f;\n\t\tgridblock.val_1d(_3, cell_id_in_block) = 0.f;\n\t}\n}\ntemplate\n__global__ void register_neighbor_blocks(uint32_t block_count, Partition partition) {\n\tuint32_t blockno = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(blockno >= block_count) {\n\t\treturn;\n\t}\n\tauto blockid = partition.active_keys[blockno];\n\tfor(char i = 0; i < 2; ++i) {\n\t\tfor(char j = 0; j < 2; ++j) {\n\t\t\tfor(char k = 0; k < 2; ++k) {\n\t\t\t\tpartition.insert(ivec3 {blockid[0] + i, blockid[1] + j, blockid[2] + k});\n\t\t\t}\n\t\t}\n\t}\n}\ntemplate\n__global__ void register_exterior_blocks(uint32_t block_count, Partition partition) {\n\tuint32_t blockno = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(blockno >= block_count) {\n\t\treturn;\n\t}\n\tauto blockid = partition.active_keys[blockno];\n\tfor(char i = -1; i < 2; ++i) {\n\t\tfor(char j = -1; j < 2; ++j) {\n\t\t\tfor(char k = -1; k < 2; ++k) {\n\t\t\t\tpartition.insert(ivec3 {blockid[0] + i, blockid[1] + j, blockid[2] + k});\n\t\t\t}\n\t\t}\n\t}\n}\ntemplate\n__global__ void rasterize(uint32_t particle_counts, const ParticleArray particle_array, Grid grid, const Partition partition, float dt, float mass) {\n\tuint32_t particle_id = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(particle_id >= particle_counts) {\n\t\treturn;\n\t}\n\n\tvec3 local_pos {particle_array.val(_0, particle_id), particle_array.val(_1, particle_id), particle_array.val(_2, particle_id)};\n\tvec3 vel;\n\tvec9 contrib;\n\tvec9 c;\n\tvel.set(0.0f), contrib.set(0.f), c.set(0.f);\n\tcontrib = (c * mass - contrib * dt) * config::G_D_INV;\n\tivec3 global_base_index {static_cast(std::lround(local_pos[0] * config::G_DX_INV) - 1), static_cast(std::lround(local_pos[1] * config::G_DX_INV) - 1), static_cast(std::lround(local_pos[2] * config::G_DX_INV) - 1)};\n\tlocal_pos = local_pos - global_base_index * config::G_DX;\n\tvec dws;\n\tfor(int d = 0; d < 3; ++d) {\n\t\tdws[d] = bspline_weight(local_pos[d]);\n\t}\n\tfor(int i = 0; i < 3; ++i) {\n\t\tfor(int j = 0; j < 3; ++j) {\n\t\t\tfor(int k = 0; k < 3; ++k) {\n\t\t\t\tivec3 offset {i, j, k};\n\t\t\t\tvec3 xixp\t\t = offset * config::G_DX - local_pos;\n\t\t\t\tfloat w\t\t\t = dws[0][i] * dws[1][j] * dws[2][k];\n\t\t\t\tivec3 local_index = global_base_index + offset;\n\t\t\t\tfloat wm\t\t = mass * w;\n\t\t\t\tint blockno\t\t = partition.query(ivec3 {static_cast(local_index[0] >> config::G_BLOCKBITS), static_cast(local_index[1] >> config::G_BLOCKBITS), static_cast(local_index[2] >> config::G_BLOCKBITS)});\n\t\t\t\tauto grid_block\t = grid.ch(_0, blockno);\n\t\t\t\tfor(int d = 0; d < 3; ++d) {\n\t\t\t\t\tlocal_index[d] = local_index[d] & config::G_BLOCKMASK;\n\t\t\t\t}\n\t\t\t\tatomicAdd(&grid_block.val(_0, local_index[0], local_index[1], local_index[2]), wm);\n\t\t\t\tatomicAdd(&grid_block.val(_1, local_index[0], local_index[1], local_index[2]), wm * vel[0] + (contrib[0] * xixp[0] + contrib[3] * xixp[1] + contrib[6] * xixp[2]) * w);\n\t\t\t\tatomicAdd(&grid_block.val(_2, local_index[0], local_index[1], local_index[2]), wm * vel[1] + (contrib[1] * xixp[0] + contrib[4] * xixp[1] + contrib[7] * xixp[2]) * w);\n\t\t\t\tatomicAdd(&grid_block.val(_3, local_index[0], local_index[1], local_index[2]), wm * vel[2] + (contrib[2] * xixp[0] + contrib[5] * xixp[1] + contrib[8] * xixp[2]) * w);\n\t\t\t}\n\t\t}\n\t}\n}\n\ntemplate\n__global__ void array_to_buffer(ParticleArray particle_array, ParticleBuffer particle_buffer, Partion partition) {\n\tuint32_t blockno\t= blockIdx.x;\n\tint particle_counts = partition.particle_bucket_sizes[blockno];\n\tauto* bucket\t\t= partition.blockbuckets + static_cast(blockno) * config::G_PARTICLE_NUM_PER_BLOCK;\n\tfor(int particle_id_in_block = static_cast(threadIdx.x); particle_id_in_block < particle_counts; particle_id_in_block += static_cast(blockDim.x)) {\n\t\tauto particle_id = bucket[particle_id_in_block];\n\t\tauto particle_bin = particle_buffer.ch(_0, partition.bin_offsets[blockno] + particle_id_in_block / config::G_BIN_CAPACITY);\n\t\t/// pos\n\t\tparticle_bin.val(_0, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_0, particle_id);\n\t\tparticle_bin.val(_1, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_1, particle_id);\n\t\tparticle_bin.val(_2, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_2, particle_id);\n\t\t/// J\n\t\tparticle_bin.val(_3, particle_id_in_block % config::G_BIN_CAPACITY) = 1.f;\n\t}\n}\n\ntemplate\n__global__ void array_to_buffer(ParticleArray particle_array, ParticleBuffer particle_buffer, Partion partition) {\n\tuint32_t blockno\t= blockIdx.x;\n\tint particle_counts = partition.particle_bucket_sizes[blockno];\n\tauto* bucket\t\t= partition.blockbuckets + static_cast(blockno) * config::G_PARTICLE_NUM_PER_BLOCK;\n\tfor(int particle_id_in_block = static_cast(threadIdx.x); particle_id_in_block < particle_counts; particle_id_in_block += static_cast(blockDim.x)) {\n\t\tauto particle_id = bucket[particle_id_in_block];\n\t\tauto particle_bin = particle_buffer.ch(_0, partition.bin_offsets[blockno] + particle_id_in_block / config::G_BIN_CAPACITY);\n\t\t/// pos\n\t\tparticle_bin.val(_0, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_0, particle_id);\n\t\tparticle_bin.val(_1, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_1, particle_id);\n\t\tparticle_bin.val(_2, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_2, particle_id);\n\t\t/// F\n\t\tparticle_bin.val(_3, particle_id_in_block % config::G_BIN_CAPACITY)\t = 1.f;\n\t\tparticle_bin.val(_4, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_5, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_6, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_7, particle_id_in_block % config::G_BIN_CAPACITY)\t = 1.f;\n\t\tparticle_bin.val(_8, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_9, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_10, particle_id_in_block % config::G_BIN_CAPACITY) = 0.f;\n\t\tparticle_bin.val(_11, particle_id_in_block % config::G_BIN_CAPACITY) = 1.f;\n\t}\n}\n\ntemplate\n__global__ void array_to_buffer(ParticleArray particle_array, ParticleBuffer particle_buffer, Partion partition) {\n\tuint32_t blockno\t= blockIdx.x;\n\tint particle_counts = partition.particle_bucket_sizes[blockno];\n\tauto* bucket\t\t= partition.blockbuckets + static_cast(blockno) * config::G_PARTICLE_NUM_PER_BLOCK;\n\tfor(int particle_id_in_block = static_cast(threadIdx.x); particle_id_in_block < particle_counts; particle_id_in_block += static_cast(blockDim.x)) {\n\t\tauto particle_id = bucket[particle_id_in_block];\n\t\tauto particle_bin = particle_buffer.ch(_0, partition.bin_offsets[blockno] + particle_id_in_block / config::G_BIN_CAPACITY);\n\t\t/// pos\n\t\tparticle_bin.val(_0, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_0, particle_id);\n\t\tparticle_bin.val(_1, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_1, particle_id);\n\t\tparticle_bin.val(_2, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_2, particle_id);\n\t\t/// F\n\t\tparticle_bin.val(_3, particle_id_in_block % config::G_BIN_CAPACITY)\t = 1.f;\n\t\tparticle_bin.val(_4, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_5, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_6, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_7, particle_id_in_block % config::G_BIN_CAPACITY)\t = 1.f;\n\t\tparticle_bin.val(_8, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_9, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_10, particle_id_in_block % config::G_BIN_CAPACITY) = 0.f;\n\t\tparticle_bin.val(_11, particle_id_in_block % config::G_BIN_CAPACITY) = 1.f;\n\t\t/// log_jp\n\t\tparticle_bin.val(_12, particle_id_in_block % config::G_BIN_CAPACITY) = ParticleBuffer::LOG_JP_0;\n\t}\n}\n\ntemplate\n__global__ void array_to_buffer(ParticleArray particle_array, ParticleBuffer particle_buffer, Partion partition) {\n\tuint32_t blockno\t= blockIdx.x;\n\tint particle_counts = partition.particle_bucket_sizes[blockno];\n\tauto* bucket\t\t= partition.blockbuckets + static_cast(blockno) * config::G_PARTICLE_NUM_PER_BLOCK;\n\tfor(int particle_id_in_block = static_cast(threadIdx.x); particle_id_in_block < particle_counts; particle_id_in_block += static_cast(blockDim.x)) {\n\t\tauto particle_id = bucket[particle_id_in_block];\n\t\tauto particle_bin = particle_buffer.ch(_0, partition.bin_offsets[blockno] + particle_id_in_block / config::G_BIN_CAPACITY);\n\t\t/// pos\n\t\tparticle_bin.val(_0, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_0, particle_id);\n\t\tparticle_bin.val(_1, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_1, particle_id);\n\t\tparticle_bin.val(_2, particle_id_in_block % config::G_BIN_CAPACITY) = particle_array.val(_2, particle_id);\n\t\t/// F\n\t\tparticle_bin.val(_3, particle_id_in_block % config::G_BIN_CAPACITY)\t = 1.f;\n\t\tparticle_bin.val(_4, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_5, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_6, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_7, particle_id_in_block % config::G_BIN_CAPACITY)\t = 1.f;\n\t\tparticle_bin.val(_8, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_9, particle_id_in_block % config::G_BIN_CAPACITY)\t = 0.f;\n\t\tparticle_bin.val(_10, particle_id_in_block % config::G_BIN_CAPACITY) = 0.f;\n\t\tparticle_bin.val(_11, particle_id_in_block % config::G_BIN_CAPACITY) = 1.f;\n\t\t/// log_jp\n\t\tparticle_bin.val(_12, particle_id_in_block % config::G_BIN_CAPACITY) = ParticleBuffer::LOG_JP_0;\n\t}\n}\n\ntemplate\n__global__ void update_grid_velocity_query_max(uint32_t block_count, Grid grid, Partition partition, float dt, float* max_vel) {\n\tconst int boundary_condition = static_cast(std::floor(config::G_BOUNDARY_CONDITION));\n\tconstexpr int NUM_WARPS\t\t = config::G_NUM_GRID_BLOCKS_PER_CUDA_BLOCK * config::G_NUM_WARPS_PER_GRID_BLOCK;\n\tconstexpr unsigned ACTIVE_MASK = 0xffffffff;\n\t//__shared__ float sh_maxvels[config::G_BLOCKVOLUME * config::G_NUM_GRID_BLOCKS_PER_CUDA_BLOCK\n\t/// 32];\n\textern __shared__ float sh_maxvels[];//NOLINT(modernize-avoid-c-arrays, readability-redundant-declaration) Cannot declare runtime size shared memory as std::array; extern has different meaning here\n\tint blockno\t\t= static_cast(blockIdx.x) * config::G_NUM_GRID_BLOCKS_PER_CUDA_BLOCK + static_cast(threadIdx.x) / 32 / config::G_NUM_WARPS_PER_GRID_BLOCK;\n\tauto blockid\t= partition.active_keys[blockno];\n\tint is_in_bound = ((blockid[0] < boundary_condition || blockid[0] >= config::G_GRID_SIZE - boundary_condition) << 2) | ((blockid[1] < boundary_condition || blockid[1] >= config::G_GRID_SIZE - boundary_condition) << 1) | (blockid[2] < boundary_condition || blockid[2] >= config::G_GRID_SIZE - boundary_condition);\n\tif(threadIdx.x < NUM_WARPS) {\n\t\tsh_maxvels[threadIdx.x] = 0.0f;\n\t}\n\t__syncthreads();\n\n\t/// within-warp computations\n\tif(blockno < block_count) {\n\t\tauto grid_block = grid.ch(_0, blockno);\n\t\tfor(int cell_id_in_block = static_cast(threadIdx.x % 32); cell_id_in_block < config::G_BLOCKVOLUME; cell_id_in_block += 32) {\n\t\t\tfloat mass\t = grid_block.val_1d(_0, cell_id_in_block);\n\t\t\tfloat vel_sqr = 0.0f;\n\t\t\tvec3 vel;\n\t\t\tif(mass > 0.0f) {\n\t\t\t\tmass = 1.f / mass;\n\n\t\t\t\t//int i = (cell_id_in_block >> (config::G_BLOCKBITS << 1)) & config::G_BLOCKMASK;\n\t\t\t\t//int j = (cell_id_in_block >> config::G_BLOCKBITS) & config::G_BLOCKMASK;\n\t\t\t\t//int k = cell_id_in_block & config::G_BLOCKMASK;\n\n\t\t\t\tvel[0] = grid_block.val_1d(_1, cell_id_in_block);\n\t\t\t\tvel[1] = grid_block.val_1d(_2, cell_id_in_block);\n\t\t\t\tvel[2] = grid_block.val_1d(_3, cell_id_in_block);\n\n\t\t\t\tvel[0] = is_in_bound & 4 ? 0.0f : vel[0] * mass;\n\t\t\t\tvel[1] = is_in_bound & 2 ? 0.0f : vel[1] * mass;\n\t\t\t\tvel[1] += config::G_GRAVITY * dt;\n\t\t\t\tvel[2] = is_in_bound & 1 ? 0.0f : vel[2] * mass;\n\t\t\t\t// if (is_in_bound) ///< sticky\n\t\t\t\t// vel.set(0.f);\n\n\t\t\t\tgrid_block.val_1d(_1, cell_id_in_block) = vel[0];\n\t\t\t\tvel_sqr += vel[0] * vel[0];\n\n\t\t\t\tgrid_block.val_1d(_2, cell_id_in_block) = vel[1];\n\t\t\t\tvel_sqr += vel[1] * vel[1];\n\n\t\t\t\tgrid_block.val_1d(_3, cell_id_in_block) = vel[2];\n\t\t\t\tvel_sqr += vel[2] * vel[2];\n\t\t\t}\n\t\t\t// unsigned activeMask = __ballot_sync(0xffffffff, mv[0] != 0.0f);\n\t\t\tfor(int iter = 1; iter % 32; iter <<= 1) {\n\t\t\t\tfloat tmp = __shfl_down_sync(ACTIVE_MASK, vel_sqr, iter, 32);\n\t\t\t\tif((threadIdx.x % 32) + iter < 32) {\n\t\t\t\t\tvel_sqr = tmp > vel_sqr ? tmp : vel_sqr;\n\t\t\t\t}\n\t\t\t}\n\t\t\tif(vel_sqr > sh_maxvels[threadIdx.x / 32] && (threadIdx.x % 32) == 0) {\n\t\t\t\tsh_maxvels[threadIdx.x / 32] = vel_sqr;\n\t\t\t}\n\t\t}\n\t}\n\t__syncthreads();\n\t/// various assumptions\n\tfor(int interval = NUM_WARPS >> 1; interval > 0; interval >>= 1) {\n\t\tif(threadIdx.x < interval) {\n\t\t\tif(sh_maxvels[static_cast(threadIdx.x) + interval] > sh_maxvels[threadIdx.x]) {\n\t\t\t\tsh_maxvels[threadIdx.x] = sh_maxvels[static_cast(threadIdx.x) + interval];\n\t\t\t}\n\t\t}\n\t\t__syncthreads();\n\t}\n\tif(threadIdx.x == 0) {\n\t\tatomic_max(max_vel, sh_maxvels[0]);\n\t}\n}\n\ntemplate\n__global__ void update_grid_velocity_query_max(uint32_t block_count, Grid grid, Partition partition, float dt, Boundary boundary, float* max_vel) {\n\tconst int boundary_condition = static_cast(std::floor(config::G_BOUNDARY_CONDITION));\n\tconstexpr int NUM_WARPS\t\t = config::G_NUM_GRID_BLOCKS_PER_CUDA_BLOCK * config::G_NUM_WARPS_PER_GRID_BLOCK;\n\tconstexpr unsigned ACTIVE_MASK = 0xffffffff;\n\t//__shared__ float sh_maxvels[config::G_BLOCKVOLUME * config::G_NUM_GRID_BLOCKS_PER_CUDA_BLOCK\n\t/// 32];\n\textern __shared__ float sh_maxvels[];//NOLINT(modernize-avoid-c-arrays, readability-redundant-declaration) Cannot declare runtime size shared memory as std::array; extern has different meaning here\n\tint blockno\t\t= static_cast(blockIdx.x) * config::G_NUM_GRID_BLOCKS_PER_CUDA_BLOCK + static_cast(threadIdx.x) / 32 / config::G_NUM_WARPS_PER_GRID_BLOCK;\n\tauto blockid\t= partition.active_keys[blockno];\n\tint is_in_bound = ((blockid[0] < boundary_condition || blockid[0] >= config::G_GRID_SIZE - boundary_condition) << 2) | ((blockid[1] < boundary_condition || blockid[1] >= config::G_GRID_SIZE - boundary_condition) << 1) | (blockid[2] < boundary_condition || blockid[2] >= config::G_GRID_SIZE - boundary_condition);\n\tif(threadIdx.x < NUM_WARPS) {\n\t\tsh_maxvels[threadIdx.x] = 0.0f;\n\t}\n\t__syncthreads();\n\n\t/// within-warp computations\n\tif(blockno < block_count) {\n\t\tauto grid_block = grid.ch(_0, blockno);\n\t\tfor(int cell_id_in_block = static_cast(threadIdx.x % 32); cell_id_in_block < config::G_BLOCKVOLUME; cell_id_in_block += 32) {\n\t\t\tfloat mass\t = grid_block.val_1d(_0, cell_id_in_block);\n\t\t\tfloat vel_sqr = 0.0f;\n\t\t\tvec3 vel;\n\t\t\tif(mass > 0.0f) {\n\t\t\t\tmass = 1.f / mass;\n\n\t\t\t\t//int i = (cell_id_in_block >> (config::G_BLOCKBITS << 1)) & config::G_BLOCKMASK;\n\t\t\t\t//int j = (cell_id_in_block >> config::G_BLOCKBITS) & config::G_BLOCKMASK;\n\t\t\t\t//int k = cell_id_in_block & config::G_BLOCKMASK;\n\n\t\t\t\tvel[0] = grid_block.val_1d(_1, cell_id_in_block);\n\t\t\t\tvel[1] = grid_block.val_1d(_2, cell_id_in_block);\n\t\t\t\tvel[2] = grid_block.val_1d(_3, cell_id_in_block);\n\n\t\t\t\tvel[0] = is_in_bound & 4 ? 0.0f : vel[0] * mass;\n\t\t\t\tvel[1] = is_in_bound & 2 ? 0.0f : vel[1] * mass;\n\t\t\t\tvel[1] += config::G_GRAVITY * dt;\n\t\t\t\tvel[2] = is_in_bound & 1 ? 0.0f : vel[2] * mass;\n\n\t\t\t\tivec3 cellid {(cell_id_in_block & 0x30) >> 4, (cell_id_in_block & 0xc) >> 2, cell_id_in_block & 0x3};\n\t\t\t\tboundary.detect_and_resolve_collision(blockid, cellid, 0.f, vel);\n\t\t\t\tvel_sqr\t\t\t\t\t\t\t\t\t= vel.dot(vel);\n\t\t\t\tgrid_block.val_1d(_1, cell_id_in_block) = vel[0];\n\t\t\t\tvel_sqr += vel[0] * vel[0];\n\n\t\t\t\tgrid_block.val_1d(_2, cell_id_in_block) = vel[1];\n\t\t\t\tvel_sqr += vel[1] * vel[1];\n\n\t\t\t\tgrid_block.val_1d(_3, cell_id_in_block) = vel[2];\n\t\t\t\tvel_sqr += vel[2] * vel[2];\n\t\t\t}\n\t\t\t// unsigned activeMask = __ballot_sync(0xffffffff, mv[0] != 0.0f);\n\t\t\tfor(int iter = 1; iter % 32; iter <<= 1) {\n\t\t\t\tfloat tmp = __shfl_down_sync(ACTIVE_MASK, vel_sqr, iter, 32);\n\t\t\t\tif((threadIdx.x % 32) + iter < 32) {\n\t\t\t\t\tvel_sqr = tmp > vel_sqr ? tmp : vel_sqr;\n\t\t\t\t}\n\t\t\t}\n\t\t\tif(vel_sqr > sh_maxvels[threadIdx.x / 32] && (threadIdx.x % 32) == 0) {\n\t\t\t\tsh_maxvels[threadIdx.x / 32] = vel_sqr;\n\t\t\t}\n\t\t}\n\t}\n\t__syncthreads();\n\t/// various assumptions\n\tfor(int interval = NUM_WARPS >> 1; interval > 0; interval >>= 1) {\n\t\tif(threadIdx.x < interval) {\n\t\t\tif(sh_maxvels[static_cast(threadIdx.x) + interval] > sh_maxvels[threadIdx.x]) {\n\t\t\t\tsh_maxvels[threadIdx.x] = sh_maxvels[static_cast(threadIdx.x) + interval];\n\t\t\t}\n\t\t}\n\t\t__syncthreads();\n\t}\n\tif(threadIdx.x == 0) {\n\t\tatomic_max(max_vel, sh_maxvels[0]);\n\t}\n}\n\ntemplate\n__global__ void g2p2g(float dt, float new_dt, const ivec3* __restrict__ blocks, const ParticleBuffer particle_buffer, ParticleBuffer next_particle_buffer, const Partition prev_partition, Partition partition, const Grid grid, Grid next_grid) {\n\tstatic constexpr uint64_t NUM_VI_PER_BLOCK = static_cast(config::G_BLOCKVOLUME) * 3;\n\tstatic constexpr uint64_t NUM_VI_IN_ARENA = NUM_VI_PER_BLOCK << 3;\n\n\tstatic constexpr uint64_t NUM_M_VI_PER_BLOCK = static_cast(config::G_BLOCKVOLUME) * 4;\n\tstatic constexpr uint64_t NUM_M_VI_IN_ARENA\t = NUM_M_VI_PER_BLOCK << 3;\n\n\tstatic constexpr unsigned ARENAMASK = (config::G_BLOCKSIZE << 1) - 1;\n\tstatic constexpr unsigned ARENABITS = config::G_BLOCKBITS + 1;\n\n\tusing ViArena\t = std::array, config::G_BLOCKSIZE << 1>, config::G_BLOCKSIZE << 1>, 3>*;\n\tusing ViArenaRef = std::array, config::G_BLOCKSIZE << 1>, config::G_BLOCKSIZE << 1>, 3>&;\n\tusing MViArena\t = std::array, config::G_BLOCKSIZE << 1>, config::G_BLOCKSIZE << 1>, 4>*;\n\tusing MViArenaRef = std::array, config::G_BLOCKSIZE << 1>, config::G_BLOCKSIZE << 1>, 4>&;\n\n\textern __shared__ char shmem[];//NOLINT(modernize-avoid-c-arrays, readability-redundant-declaration) Cannot declare runtime size shared memory as std::array; extern has different meaning here\n\n\tViArenaRef __restrict__ g2pbuffer = *static_cast(static_cast(static_cast(shmem)));\n\tMViArenaRef __restrict__ p2gbuffer = *static_cast(static_cast(static_cast(shmem) + NUM_VI_IN_ARENA * sizeof(float)));\n\n\tivec3 blockid;\n\tint src_blockno;\n\tif(blocks != nullptr) {\n\t\tblockid\t\t= blocks[blockIdx.x];\n\t\tsrc_blockno = partition.query(blockid);\n\t} else {\n\t\tif(partition.halo_marks[blockIdx.x]) {\n\t\t\treturn;\n\t\t}\n\t\tblockid = partition.active_keys[blockIdx.x];\n\n\t\tint src_blockno\t\t\t = static_cast(blockIdx.x);\n\t\tint particle_bucket_size = next_particle_buffer.particle_bucket_sizes[src_blockno];\n\t\tif(particle_bucket_size == 0) {\n\t\t\treturn;\n\t\t}\n\t}\n\n\tfor(int base = static_cast(threadIdx.x); base < NUM_VI_IN_ARENA; base += static_cast(blockDim.x)) {\n\t\tchar local_block_id = static_cast(base / NUM_VI_PER_BLOCK);\n\t\tauto blockno\t\t= partition.query(ivec3 {blockid[0] + ((local_block_id & 4) != 0 ? 1 : 0), blockid[1] + ((local_block_id & 2) != 0 ? 1 : 0), blockid[2] + ((local_block_id & 1) != 0 ? 1 : 0)});\n\t\tauto grid_block\t\t= grid.ch(_0, blockno);\n\t\tint channelid\t\t= static_cast(base % NUM_VI_PER_BLOCK);\n\t\tchar c\t\t\t\t= static_cast(channelid & 0x3f);\n\n\t\tchar cz = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tchar cy = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tchar cx = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tfloat val;\n\t\tif(channelid == 0) {\n\t\t\tval = grid_block.val_1d(_1, c);\n\t\t} else if(channelid == 1) {\n\t\t\tval = grid_block.val_1d(_2, c);\n\t\t} else {\n\t\t\tval = grid_block.val_1d(_3, c);\n\t\t}\n\t\tg2pbuffer[channelid][static_cast(static_cast(cx) + (local_block_id & 4 ? config::G_BLOCKSIZE : 0))][static_cast(static_cast(cy) + (local_block_id & 2 ? config::G_BLOCKSIZE : 0))][static_cast(static_cast(cz) + (local_block_id & 1 ? config::G_BLOCKSIZE : 0))] = val;\n\t}\n\t__syncthreads();\n\tfor(int base = static_cast(threadIdx.x); base < NUM_M_VI_IN_ARENA; base += static_cast(blockDim.x)) {\n\t\tint loc = base;\n\t\tchar z\t= static_cast(loc & ARENAMASK);\n\t\tloc >>= ARENABITS;\n\n\t\tchar y = static_cast(loc & ARENAMASK);\n\t\tloc >>= ARENABITS;\n\n\t\tchar x\t\t\t\t\t\t\t\t = static_cast(loc & ARENAMASK);\n\t\tp2gbuffer[loc >> ARENABITS][x][y][z] = 0.0f;\n\t}\n\t__syncthreads();\n\n\tfor(int particle_id_in_block = static_cast(threadIdx.x); particle_id_in_block < partition.particle_bucket_sizes[src_blockno]; particle_id_in_block += static_cast(blockDim.x)) {\n\t\tint advection_source_blockno;\n\t\tint source_pidib;\n\t\tivec3 base_index;\n\t\t{\n\t\t\tint advect = partition.blockbuckets[src_blockno * config::G_PARTICLE_NUM_PER_BLOCK + particle_id_in_block];\n\t\t\tdir_components(advect / config::G_PARTICLE_NUM_PER_BLOCK, base_index);\n\t\t\tbase_index += blockid;\n\t\t\tadvection_source_blockno = prev_partition.query(base_index);\n\t\t\tsource_pidib\t\t\t = advect & (config::G_PARTICLE_NUM_PER_BLOCK - 1);\n\t\t\tadvection_source_blockno = prev_partition.bin_offsets[advection_source_blockno] + source_pidib / config::G_BIN_CAPACITY;\n\t\t}\n\t\tvec3 pos;\n\t\tfloat J;\n\t\t{\n\t\t\tauto source_particle_bin = particle_buffer.ch(_0, advection_source_blockno);\n\t\t\tpos[0]\t\t\t\t\t = source_particle_bin.val(_0, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tpos[1]\t\t\t\t\t = source_particle_bin.val(_1, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tpos[2]\t\t\t\t\t = source_particle_bin.val(_2, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tJ\t\t\t\t\t\t = source_particle_bin.val(_3, source_pidib % config::G_BIN_CAPACITY);\n\t\t}\n\t\tivec3 local_base_index = (pos * config::G_DX_INV + 0.5f).cast() - 1;\n\t\tvec3 local_pos\t\t = pos - local_base_index * config::G_DX;\n\t\tbase_index\t\t\t = local_base_index;\n\n\t\tvec3x3 dws;\n#pragma unroll 3\n\t\tfor(int dd = 0; dd < 3; ++dd) {\n\t\t\tfloat d\t = (local_pos[dd] - static_cast(std::floor(local_pos[dd] * config::G_DX_INV + 0.5f) - 1) * config::G_DX) * config::G_DX_INV;\n\t\t\tdws(dd, 0) = 0.5f * (1.5f - d) * (1.5f - d);\n\t\t\td -= 1.0f;\n\t\t\tdws(dd, 1)\t\t\t = 0.75f - d * d;\n\t\t\td\t\t\t\t\t = 0.5f + d;\n\t\t\tdws(dd, 2)\t\t\t = 0.5f * d * d;\n\t\t\tlocal_base_index[dd] = ((local_base_index[dd] - 1) & config::G_BLOCKMASK) + 1;\n\t\t}\n\t\tvec3 vel;\n\t\tvel.set(0.f);\n\t\tvec9 C;\n\t\tC.set(0.f);\n#pragma unroll 3\n\t\tfor(char i = 0; i < 3; i++) {\n#pragma unroll 3\n\t\t\tfor(char j = 0; j < 3; j++) {\n#pragma unroll 3\n\t\t\t\tfor(char k = 0; k < 3; k++) {\n\t\t\t\t\tvec3 xixp = vec3 {static_cast(i), static_cast(j), static_cast(k)} * config::G_DX - local_pos;\n\t\t\t\t\tfloat W\t = dws(0, i) * dws(1, j) * dws(2, k);\n\t\t\t\t\tvec3 vi {g2pbuffer[0][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], g2pbuffer[1][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], g2pbuffer[2][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)]};\n\t\t\t\t\tvel += vi * W;\n\t\t\t\t\tC[0] += W * vi[0] * xixp[0];\n\t\t\t\t\tC[1] += W * vi[1] * xixp[0];\n\t\t\t\t\tC[2] += W * vi[2] * xixp[0];\n\t\t\t\t\tC[3] += W * vi[0] * xixp[1];\n\t\t\t\t\tC[4] += W * vi[1] * xixp[1];\n\t\t\t\t\tC[5] += W * vi[2] * xixp[1];\n\t\t\t\t\tC[6] += W * vi[0] * xixp[2];\n\t\t\t\t\tC[7] += W * vi[1] * xixp[2];\n\t\t\t\t\tC[8] += W * vi[2] * xixp[2];\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\tpos += vel * dt;\n\n\t\tJ = (1 + (C[0] + C[4] + C[8]) * dt * config::G_D_INV) * J;\n\t\tif(J < 0.1) {\n\t\t\tJ = 0.1;\n\t\t}\n\t\tvec9 contrib;\n\t\t{\n\t\t\tfloat voln\t = J * particle_buffer.volume;\n\t\t\tfloat pressure = particle_buffer.bulk * (powf(J, -particle_buffer.gamma) - 1.f);\n\t\t\t{\n\t\t\t\tcontrib[0] = ((C[0] + C[0]) * config::G_D_INV * particle_buffer.viscosity - pressure) * voln;\n\t\t\t\tcontrib[1] = (C[1] + C[3]) * config::G_D_INV * particle_buffer.viscosity * voln;\n\t\t\t\tcontrib[2] = (C[2] + C[6]) * config::G_D_INV * particle_buffer.viscosity * voln;\n\n\t\t\t\tcontrib[3] = (C[3] + C[1]) * config::G_D_INV * particle_buffer.viscosity * voln;\n\t\t\t\tcontrib[4] = ((C[4] + C[4]) * config::G_D_INV * particle_buffer.viscosity - pressure) * voln;\n\t\t\t\tcontrib[5] = (C[5] + C[7]) * config::G_D_INV * particle_buffer.viscosity * voln;\n\n\t\t\t\tcontrib[6] = (C[6] + C[2]) * config::G_D_INV * particle_buffer.viscosity * voln;\n\t\t\t\tcontrib[7] = (C[7] + C[5]) * config::G_D_INV * particle_buffer.viscosity * voln;\n\t\t\t\tcontrib[8] = ((C[8] + C[8]) * config::G_D_INV * particle_buffer.viscosity - pressure) * voln;\n\t\t\t}\n\t\t\tcontrib = (C * particle_buffer.mass - contrib * new_dt) * config::G_D_INV;\n\t\t\t{\n\t\t\t\tauto particle_bin\t\t\t\t\t\t\t\t\t\t\t\t\t= next_particle_buffer.ch(_0, partition.bin_offsets[src_blockno] + particle_id_in_block / config::G_BIN_CAPACITY);\n\t\t\t\tparticle_bin.val(_0, particle_id_in_block % config::G_BIN_CAPACITY) = pos[0];\n\t\t\t\tparticle_bin.val(_1, particle_id_in_block % config::G_BIN_CAPACITY) = pos[1];\n\t\t\t\tparticle_bin.val(_2, particle_id_in_block % config::G_BIN_CAPACITY) = pos[2];\n\t\t\t\tparticle_bin.val(_3, particle_id_in_block % config::G_BIN_CAPACITY) = J;\n\t\t\t}\n\t\t}\n\n\t\tlocal_base_index = (pos * config::G_DX_INV + 0.5f).cast() - 1;\n\t\t{\n\t\t\tint dirtag = dir_offset((base_index - 1) / static_cast(config::G_BLOCKSIZE) - (local_base_index - 1) / static_cast(config::G_BLOCKSIZE));\n\t\t\tpartition.add_advection(local_base_index - 1, dirtag, particle_id_in_block);\n\t\t}\n\t\t// dws[d] = bspline_weight(local_pos[d]);\n\n#pragma unroll 3\n\t\tfor(char dd = 0; dd < 3; ++dd) {\n\t\t\tlocal_pos[dd] = pos[dd] - static_cast(local_base_index[dd]) * config::G_DX;\n\t\t\tfloat d\t\t = (local_pos[dd] - static_cast(std::floor(local_pos[dd] * config::G_DX_INV + 0.5f) - 1) * config::G_DX) * config::G_DX_INV;\n\t\t\tdws(dd, 0)\t = 0.5f * (1.5f - d) * (1.5f - d);\n\t\t\td -= 1.0f;\n\t\t\tdws(dd, 1) = 0.75f - d * d;\n\t\t\td\t\t = 0.5f + d;\n\t\t\tdws(dd, 2) = 0.5f * d * d;\n\n\t\t\tlocal_base_index[dd] = (((base_index[dd] - 1) & config::G_BLOCKMASK) + 1) + local_base_index[dd] - base_index[dd];\n\t\t}\n#pragma unroll 3\n\t\tfor(char i = 0; i < 3; i++) {\n#pragma unroll 3\n\t\t\tfor(char j = 0; j < 3; j++) {\n#pragma unroll 3\n\t\t\t\tfor(char k = 0; k < 3; k++) {\n\t\t\t\t\tpos\t\t= vec3 {static_cast(i), static_cast(j), static_cast(k)} * config::G_DX - local_pos;\n\t\t\t\t\tfloat W = dws(0, i) * dws(1, j) * dws(2, k);\n\t\t\t\t\tauto wm = particle_buffer.mass * W;\n\t\t\t\t\tatomicAdd(&p2gbuffer[0][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], wm);\n\t\t\t\t\tatomicAdd(&p2gbuffer[1][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], wm * vel[0] + (contrib[0] * pos[0] + contrib[3] * pos[1] + contrib[6] * pos[2]) * W);\n\t\t\t\t\tatomicAdd(&p2gbuffer[2][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], wm * vel[1] + (contrib[1] * pos[0] + contrib[4] * pos[1] + contrib[7] * pos[2]) * W);\n\t\t\t\t\tatomicAdd(&p2gbuffer[3][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], wm * vel[2] + (contrib[2] * pos[0] + contrib[5] * pos[1] + contrib[8] * pos[2]) * W);\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\t__syncthreads();\n\t/// arena no, channel no, cell no\n\tfor(int base = static_cast(threadIdx.x); base < NUM_M_VI_IN_ARENA; base += static_cast(blockDim.x)) {\n\t\tchar local_block_id = static_cast(base / NUM_M_VI_PER_BLOCK);\n\t\tauto blockno\t\t= partition.query(ivec3 {blockid[0] + ((local_block_id & 4) != 0 ? 1 : 0), blockid[1] + ((local_block_id & 2) != 0 ? 1 : 0), blockid[2] + ((local_block_id & 1) != 0 ? 1 : 0)});\n\t\t// auto grid_block = next_grid.template ch<0>(blockno);\n\t\tint channelid = static_cast(base & (NUM_M_VI_PER_BLOCK - 1));\n\t\tchar c\t\t = static_cast(channelid % config::G_BLOCKVOLUME);\n\n\t\tchar cz = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tchar cy = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tchar cx = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tfloat val = p2gbuffer[channelid][static_cast(static_cast(cx) + (local_block_id & 4 ? config::G_BLOCKSIZE : 0))][static_cast(static_cast(cy) + (local_block_id & 2 ? config::G_BLOCKSIZE : 0))][static_cast(static_cast(cz) + (local_block_id & 1 ? config::G_BLOCKSIZE : 0))];\n\t\tif(channelid == 0) {\n\t\t\tatomicAdd(&next_grid.ch(_0, blockno).val_1d(_0, c), val);\n\t\t} else if(channelid == 1) {\n\t\t\tatomicAdd(&next_grid.ch(_0, blockno).val_1d(_1, c), val);\n\t\t} else if(channelid == 2) {\n\t\t\tatomicAdd(&next_grid.ch(_0, blockno).val_1d(_2, c), val);\n\t\t} else {\n\t\t\tatomicAdd(&next_grid.ch(_0, blockno).val_1d(_3, c), val);\n\t\t}\n\t}\n}\n\ntemplate\n__global__ void g2p2g(float dt, float new_dt, const ivec3* __restrict__ blocks, const ParticleBuffer particle_buffer, ParticleBuffer next_particle_buffer, const Partition prev_partition, Partition partition, const Grid grid, Grid next_grid) {\n\tstatic constexpr uint64_t NUM_VI_PER_BLOCK = static_cast(config::G_BLOCKVOLUME) * 3;\n\tstatic constexpr uint64_t NUM_VI_IN_ARENA = NUM_VI_PER_BLOCK << 3;\n\n\tstatic constexpr uint64_t NUM_M_VI_PER_BLOCK = static_cast(config::G_BLOCKVOLUME) * 4;\n\tstatic constexpr uint64_t NUM_M_VI_IN_ARENA\t = NUM_M_VI_PER_BLOCK << 3;\n\n\tstatic constexpr unsigned ARENAMASK = (config::G_BLOCKSIZE << 1) - 1;\n\tstatic constexpr unsigned ARENABITS = config::G_BLOCKBITS + 1;\n\n\tusing ViArena\t = std::array, config::G_BLOCKSIZE << 1>, config::G_BLOCKSIZE << 1>, 3>*;\n\tusing ViArenaRef = std::array, config::G_BLOCKSIZE << 1>, config::G_BLOCKSIZE << 1>, 3>&;\n\tusing MViArena\t = std::array, config::G_BLOCKSIZE << 1>, config::G_BLOCKSIZE << 1>, 4>*;\n\tusing MViArenaRef = std::array, config::G_BLOCKSIZE << 1>, config::G_BLOCKSIZE << 1>, 4>&;\n\n\textern __shared__ char shmem[];//NOLINT(modernize-avoid-c-arrays, readability-redundant-declaration) Cannot declare runtime size shared memory as std::array; extern has different meaning here\n\n\tViArenaRef __restrict__ g2pbuffer = *static_cast(static_cast(static_cast(shmem)));\n\tMViArenaRef __restrict__ p2gbuffer = *static_cast(static_cast(static_cast(shmem) + NUM_VI_IN_ARENA * sizeof(float)));\n\n\tivec3 blockid;\n\tint src_blockno;\n\tif(blocks != nullptr) {\n\t\tblockid\t\t= blocks[blockIdx.x];\n\t\tsrc_blockno = partition.query(blockid);\n\t} else {\n\t\tif(partition.halo_marks[blockIdx.x]) {\n\t\t\treturn;\n\t\t}\n\t\tblockid = partition.active_keys[blockIdx.x];\n\n\t\tint src_blockno\t\t\t = static_cast(blockIdx.x);\n\t\tint particle_bucket_size = next_particle_buffer.particle_bucket_sizes[src_blockno];\n\t\tif(particle_bucket_size == 0) {\n\t\t\treturn;\n\t\t}\n\t}\n\n\tfor(int base = static_cast(threadIdx.x); base < NUM_VI_IN_ARENA; base += static_cast(blockDim.x)) {\n\t\tchar local_block_id = static_cast(base / NUM_VI_PER_BLOCK);\n\t\tauto blockno\t\t= partition.query(ivec3 {blockid[0] + ((local_block_id & 4) != 0 ? 1 : 0), blockid[1] + ((local_block_id & 2) != 0 ? 1 : 0), blockid[2] + ((local_block_id & 1) != 0 ? 1 : 0)});\n\t\tauto grid_block\t\t= grid.ch(_0, blockno);\n\t\tint channelid\t\t= static_cast(base % NUM_VI_PER_BLOCK);\n\t\tchar c\t\t\t\t= static_cast(channelid & 0x3f);\n\n\t\tchar cz = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tchar cy = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tchar cx = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tfloat val;\n\t\tif(channelid == 0) {\n\t\t\tval = grid_block.val_1d(_1, c);\n\t\t} else if(channelid == 1) {\n\t\t\tval = grid_block.val_1d(_2, c);\n\t\t} else {\n\t\t\tval = grid_block.val_1d(_3, c);\n\t\t}\n\t\tg2pbuffer[channelid][static_cast(static_cast(cx) + (local_block_id & 4 ? config::G_BLOCKSIZE : 0))][static_cast(static_cast(cy) + (local_block_id & 2 ? config::G_BLOCKSIZE : 0))][static_cast(static_cast(cz) + (local_block_id & 1 ? config::G_BLOCKSIZE : 0))] = val;\n\t}\n\t__syncthreads();\n\tfor(int base = static_cast(threadIdx.x); base < NUM_M_VI_IN_ARENA; base += static_cast(blockDim.x)) {\n\t\tint loc = static_cast(base);\n\n\t\tchar z = static_cast(loc & ARENAMASK);\n\t\tloc >>= ARENABITS;\n\n\t\tchar y = static_cast(loc & ARENAMASK);\n\t\tloc >>= ARENABITS;\n\n\t\tchar x\t\t\t\t\t\t\t\t = static_cast(loc & ARENAMASK);\n\t\tp2gbuffer[loc >> ARENABITS][x][y][z] = 0.0f;\n\t}\n\t__syncthreads();\n\n\tfor(int particle_id_in_block = static_cast(threadIdx.x); particle_id_in_block < partition.particle_bucket_sizes[src_blockno]; particle_id_in_block += static_cast(blockDim.x)) {\n\t\tint advection_source_blockno;\n\t\tint source_pidib;\n\t\tivec3 base_index;\n\t\t{\n\t\t\tint advect = partition.blockbuckets[src_blockno * config::G_PARTICLE_NUM_PER_BLOCK + particle_id_in_block];\n\t\t\tdir_components(advect / config::G_PARTICLE_NUM_PER_BLOCK, base_index);\n\t\t\tbase_index += blockid;\n\t\t\tadvection_source_blockno = prev_partition.query(base_index);\n\t\t\tsource_pidib\t\t\t = advect & (config::G_PARTICLE_NUM_PER_BLOCK - 1);\n\t\t\tadvection_source_blockno = prev_partition.bin_offsets[advection_source_blockno] + source_pidib / config::G_BIN_CAPACITY;\n\t\t}\n\t\tvec3 pos;\n\t\t{\n\t\t\tauto source_particle_bin = particle_buffer.ch(_0, advection_source_blockno);\n\t\t\tpos[0]\t\t\t\t\t = source_particle_bin.val(_0, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tpos[1]\t\t\t\t\t = source_particle_bin.val(_1, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tpos[2]\t\t\t\t\t = source_particle_bin.val(_2, source_pidib % config::G_BIN_CAPACITY);\n\t\t}\n\t\tivec3 local_base_index = (pos * config::G_DX_INV + 0.5f).cast() - 1;\n\t\tvec3 local_pos\t\t = pos - local_base_index * config::G_DX;\n\t\tbase_index\t\t\t = local_base_index;\n\n\t\tvec3x3 dws;\n#pragma unroll 3\n\t\tfor(int dd = 0; dd < 3; ++dd) {\n\t\t\tfloat d\t = (local_pos[dd] - static_cast(std::floor(local_pos[dd] * config::G_DX_INV + 0.5f) - 1) * config::G_DX) * config::G_DX_INV;\n\t\t\tdws(dd, 0) = 0.5f * (1.5f - d) * (1.5f - d);\n\t\t\td -= 1.0f;\n\t\t\tdws(dd, 1)\t\t\t = 0.75f - d * d;\n\t\t\td\t\t\t\t\t = 0.5f + d;\n\t\t\tdws(dd, 2)\t\t\t = 0.5f * d * d;\n\t\t\tlocal_base_index[dd] = ((local_base_index[dd] - 1) & config::G_BLOCKMASK) + 1;\n\t\t}\n\t\tvec3 vel;\n\t\tvel.set(0.f);\n\t\tvec9 C;\n\t\tC.set(0.f);\n#pragma unroll 3\n\t\tfor(char i = 0; i < 3; i++) {\n#pragma unroll 3\n\t\t\tfor(char j = 0; j < 3; j++) {\n#pragma unroll 3\n\t\t\t\tfor(char k = 0; k < 3; k++) {\n\t\t\t\t\tvec3 xixp = vec3 {static_cast(i), static_cast(j), static_cast(k)} * config::G_DX - local_pos;\n\t\t\t\t\tfloat W\t = dws(0, i) * dws(1, j) * dws(2, k);\n\t\t\t\t\tvec3 vi {g2pbuffer[0][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], g2pbuffer[1][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], g2pbuffer[2][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)]};\n\t\t\t\t\tvel += vi * W;\n\t\t\t\t\tC[0] += W * vi[0] * xixp[0];\n\t\t\t\t\tC[1] += W * vi[1] * xixp[0];\n\t\t\t\t\tC[2] += W * vi[2] * xixp[0];\n\t\t\t\t\tC[3] += W * vi[0] * xixp[1];\n\t\t\t\t\tC[4] += W * vi[1] * xixp[1];\n\t\t\t\t\tC[5] += W * vi[2] * xixp[1];\n\t\t\t\t\tC[6] += W * vi[0] * xixp[2];\n\t\t\t\t\tC[7] += W * vi[1] * xixp[2];\n\t\t\t\t\tC[8] += W * vi[2] * xixp[2];\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\tpos += vel * dt;\n\n#pragma unroll 9\n\t\tfor(int d = 0; d < 9; ++d) {\n\t\t\tdws.val(d) = C[d] * dt * config::G_D_INV + ((d & 0x3) ? 0.f : 1.f);\n\t\t}\n\n\t\tvec9 contrib;\n\t\t{\n\t\t\tvec9 F;\n\t\t\tauto source_particle_bin = particle_buffer.ch(_0, advection_source_blockno);\n\t\t\tcontrib[0]\t\t\t\t = source_particle_bin.val(_3, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[1]\t\t\t\t = source_particle_bin.val(_4, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[2]\t\t\t\t = source_particle_bin.val(_5, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[3]\t\t\t\t = source_particle_bin.val(_6, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[4]\t\t\t\t = source_particle_bin.val(_7, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[5]\t\t\t\t = source_particle_bin.val(_8, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[6]\t\t\t\t = source_particle_bin.val(_9, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[7]\t\t\t\t = source_particle_bin.val(_10, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[8]\t\t\t\t = source_particle_bin.val(_11, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tmatrix_matrix_multiplication_3d(dws.data_arr(), contrib.data_arr(), F.data_arr());\n\t\t\t{\n\t\t\t\tauto particle_bin\t\t\t\t\t\t\t\t\t\t\t\t\t = next_particle_buffer.ch(_0, partition.bin_offsets[src_blockno] + particle_id_in_block / config::G_BIN_CAPACITY);\n\t\t\t\tparticle_bin.val(_0, particle_id_in_block % config::G_BIN_CAPACITY)\t = pos[0];\n\t\t\t\tparticle_bin.val(_1, particle_id_in_block % config::G_BIN_CAPACITY)\t = pos[1];\n\t\t\t\tparticle_bin.val(_2, particle_id_in_block % config::G_BIN_CAPACITY)\t = pos[2];\n\t\t\t\tparticle_bin.val(_3, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[0];\n\t\t\t\tparticle_bin.val(_4, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[1];\n\t\t\t\tparticle_bin.val(_5, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[2];\n\t\t\t\tparticle_bin.val(_6, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[3];\n\t\t\t\tparticle_bin.val(_7, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[4];\n\t\t\t\tparticle_bin.val(_8, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[5];\n\t\t\t\tparticle_bin.val(_9, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[6];\n\t\t\t\tparticle_bin.val(_10, particle_id_in_block % config::G_BIN_CAPACITY) = F[7];\n\t\t\t\tparticle_bin.val(_11, particle_id_in_block % config::G_BIN_CAPACITY) = F[8];\n\t\t\t}\n\t\t\tcompute_stress_fixed_corotated(particle_buffer.volume, particle_buffer.mu, particle_buffer.lambda, F, contrib);\n\t\t\tcontrib = (C * particle_buffer.mass - contrib * new_dt) * config::G_D_INV;\n\t\t}\n\n\t\tlocal_base_index = (pos * config::G_DX_INV + 0.5f).cast() - 1;\n\t\t{\n\t\t\tint dirtag = dir_offset((base_index - 1) / static_cast(config::G_BLOCKSIZE) - (local_base_index - 1) / static_cast(config::G_BLOCKSIZE));\n\t\t\tpartition.add_advection(local_base_index - 1, dirtag, particle_id_in_block);\n\t\t}\n\t\t// dws[d] = bspline_weight(local_pos[d]);\n\n#pragma unroll 3\n\t\tfor(char dd = 0; dd < 3; ++dd) {\n\t\t\tlocal_pos[dd] = pos[dd] - static_cast(local_base_index[dd]) * config::G_DX;\n\t\t\tfloat d\t\t = (local_pos[dd] - static_cast(std::floor(local_pos[dd] * config::G_DX_INV + 0.5f) - 1) * config::G_DX) * config::G_DX_INV;\n\t\t\tdws(dd, 0)\t = 0.5f * (1.5f - d) * (1.5f - d);\n\t\t\td -= 1.0f;\n\t\t\tdws(dd, 1) = 0.75f - d * d;\n\t\t\td\t\t = 0.5f + d;\n\t\t\tdws(dd, 2) = 0.5f * d * d;\n\n\t\t\tlocal_base_index[dd] = (((base_index[dd] - 1) & config::G_BLOCKMASK) + 1) + local_base_index[dd] - base_index[dd];\n\t\t}\n#pragma unroll 3\n\t\tfor(char i = 0; i < 3; i++) {\n#pragma unroll 3\n\t\t\tfor(char j = 0; j < 3; j++) {\n#pragma unroll 3\n\t\t\t\tfor(char k = 0; k < 3; k++) {\n\t\t\t\t\tpos\t\t= vec3 {static_cast(i), static_cast(j), static_cast(k)} * config::G_DX - local_pos;\n\t\t\t\t\tfloat W = dws(0, i) * dws(1, j) * dws(2, k);\n\t\t\t\t\tauto wm = particle_buffer.mass * W;\n\t\t\t\t\tatomicAdd(&p2gbuffer[0][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], wm);\n\t\t\t\t\tatomicAdd(&p2gbuffer[1][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], wm * vel[0] + (contrib[0] * pos[0] + contrib[3] * pos[1] + contrib[6] * pos[2]) * W);\n\t\t\t\t\tatomicAdd(&p2gbuffer[2][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], wm * vel[1] + (contrib[1] * pos[0] + contrib[4] * pos[1] + contrib[7] * pos[2]) * W);\n\t\t\t\t\tatomicAdd(&p2gbuffer[3][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], wm * vel[2] + (contrib[2] * pos[0] + contrib[5] * pos[1] + contrib[8] * pos[2]) * W);\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\t__syncthreads();\n\t/// arena no, channel no, cell no\n\tfor(int base = static_cast(threadIdx.x); base < NUM_M_VI_IN_ARENA; base += static_cast(blockDim.x)) {\n\t\tchar local_block_id = static_cast(base / NUM_M_VI_PER_BLOCK);\n\t\tauto blockno\t\t= partition.query(ivec3 {blockid[0] + ((local_block_id & 4) != 0 ? 1 : 0), blockid[1] + ((local_block_id & 2) != 0 ? 1 : 0), blockid[2] + ((local_block_id & 1) != 0 ? 1 : 0)});\n\t\t// auto grid_block = next_grid.template ch<0>(blockno);\n\t\tint channelid = static_cast(base & (NUM_M_VI_PER_BLOCK - 1));\n\t\tchar c\t\t = static_cast(channelid % config::G_BLOCKVOLUME);\n\n\t\tchar cz = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tchar cy = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tchar cx = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\t\tfloat val = p2gbuffer[channelid][static_cast(static_cast(cx) + (local_block_id & 4 ? config::G_BLOCKSIZE : 0))][static_cast(static_cast(cy) + (local_block_id & 2 ? config::G_BLOCKSIZE : 0))][static_cast(static_cast(cz) + (local_block_id & 1 ? config::G_BLOCKSIZE : 0))];\n\t\tif(channelid == 0) {\n\t\t\tatomicAdd(&next_grid.ch(_0, blockno).val_1d(_0, c), val);\n\t\t} else if(channelid == 1) {\n\t\t\tatomicAdd(&next_grid.ch(_0, blockno).val_1d(_1, c), val);\n\t\t} else if(channelid == 2) {\n\t\t\tatomicAdd(&next_grid.ch(_0, blockno).val_1d(_2, c), val);\n\t\t} else {\n\t\t\tatomicAdd(&next_grid.ch(_0, blockno).val_1d(_3, c), val);\n\t\t}\n\t}\n}\n\ntemplate\n__global__ void g2p2g(float dt, float new_dt, const ivec3* __restrict__ blocks, const ParticleBuffer particle_buffer, ParticleBuffer next_particle_buffer, const Partition prev_partition, Partition partition, const Grid grid, Grid next_grid) {\n\tstatic constexpr uint64_t NUM_VI_PER_BLOCK = static_cast(config::G_BLOCKVOLUME) * 3;\n\tstatic constexpr uint64_t NUM_VI_IN_ARENA = NUM_VI_PER_BLOCK << 3;\n\n\tstatic constexpr uint64_t NUM_M_VI_PER_BLOCK = static_cast(config::G_BLOCKVOLUME) * 4;\n\tstatic constexpr uint64_t NUM_M_VI_IN_ARENA\t = NUM_M_VI_PER_BLOCK << 3;\n\n\tstatic constexpr unsigned ARENAMASK = (config::G_BLOCKSIZE << 1) - 1;\n\tstatic constexpr unsigned ARENABITS = config::G_BLOCKBITS + 1;\n\n\tusing ViArena\t = std::array, config::G_BLOCKSIZE << 1>, config::G_BLOCKSIZE << 1>, 3>*;\n\tusing ViArenaRef = std::array, config::G_BLOCKSIZE << 1>, config::G_BLOCKSIZE << 1>, 3>&;\n\tusing MViArena\t = std::array, config::G_BLOCKSIZE << 1>, config::G_BLOCKSIZE << 1>, 4>*;\n\tusing MViArenaRef = std::array, config::G_BLOCKSIZE << 1>, config::G_BLOCKSIZE << 1>, 4>&;\n\n\textern __shared__ char shmem[];//NOLINT(modernize-avoid-c-arrays, readability-redundant-declaration) Cannot declare runtime size shared memory as std::array; extern has different meaning here\n\n\tViArenaRef __restrict__ g2pbuffer = *static_cast(static_cast(static_cast(shmem)));\n\tMViArenaRef __restrict__ p2gbuffer = *static_cast(static_cast(static_cast(shmem) + NUM_VI_IN_ARENA * sizeof(float)));\n\n\tivec3 blockid;\n\tint src_blockno;\n\tif(blocks != nullptr) {\n\t\tblockid\t\t= blocks[blockIdx.x];\n\t\tsrc_blockno = partition.query(blockid);\n\t} else {\n\t\tif(partition.halo_marks[blockIdx.x]) {\n\t\t\treturn;\n\t\t}\n\t\tblockid = partition.active_keys[blockIdx.x];\n\n\t\tint src_blockno\t\t\t = static_cast(blockIdx.x);\n\t\tint particle_bucket_size = next_particle_buffer.particle_bucket_sizes[src_blockno];\n\t\tif(particle_bucket_size == 0) {\n\t\t\treturn;\n\t\t}\n\t}\n\n\tfor(int base = static_cast(threadIdx.x); base < NUM_VI_IN_ARENA; base += static_cast(blockDim.x)) {\n\t\tchar local_block_id = static_cast(base / NUM_VI_PER_BLOCK);\n\t\tauto blockno\t\t= partition.query(ivec3 {blockid[0] + ((local_block_id & 4) != 0 ? 1 : 0), blockid[1] + ((local_block_id & 2) != 0 ? 1 : 0), blockid[2] + ((local_block_id & 1) != 0 ? 1 : 0)});\n\t\tauto grid_block\t\t= grid.ch(_0, blockno);\n\t\tint channelid\t\t= static_cast(base % NUM_VI_PER_BLOCK);\n\t\tchar c\t\t\t\t= static_cast(channelid & 0x3f);\n\n\t\tchar cz = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tchar cy = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tchar cx = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tfloat val;\n\t\tif(channelid == 0) {\n\t\t\tval = grid_block.val_1d(_1, c);\n\t\t} else if(channelid == 1) {\n\t\t\tval = grid_block.val_1d(_2, c);\n\t\t} else {\n\t\t\tval = grid_block.val_1d(_3, c);\n\t\t}\n\t\tg2pbuffer[channelid][static_cast(static_cast(cx) + (local_block_id & 4 ? config::G_BLOCKSIZE : 0))][static_cast(static_cast(cy) + (local_block_id & 2 ? config::G_BLOCKSIZE : 0))][static_cast(static_cast(cz) + (local_block_id & 1 ? config::G_BLOCKSIZE : 0))] = val;\n\t}\n\t__syncthreads();\n\tfor(int base = static_cast(threadIdx.x); base < NUM_M_VI_IN_ARENA; base += static_cast(blockDim.x)) {\n\t\tint loc = static_cast(base);\n\t\tchar z\t= static_cast(loc & ARENAMASK);\n\t\tloc >>= ARENABITS;\n\n\t\tchar y = static_cast(loc & ARENAMASK);\n\t\tloc >>= ARENABITS;\n\n\t\tchar x\t\t\t\t\t\t\t\t = static_cast(loc & ARENAMASK);\n\t\tp2gbuffer[loc >> ARENABITS][x][y][z] = 0.0f;\n\t}\n\t__syncthreads();\n\n\tfor(int particle_id_in_block = static_cast(threadIdx.x); particle_id_in_block < partition.particle_bucket_sizes[src_blockno]; particle_id_in_block += static_cast(blockDim.x)) {\n\t\tint advection_source_blockno;\n\t\tint source_pidib;\n\t\tivec3 base_index;\n\t\t{\n\t\t\tint advect = partition.blockbuckets[src_blockno * config::G_PARTICLE_NUM_PER_BLOCK + particle_id_in_block];\n\t\t\tdir_components(advect / config::G_PARTICLE_NUM_PER_BLOCK, base_index);\n\t\t\tbase_index += blockid;\n\t\t\tadvection_source_blockno = prev_partition.query(base_index);\n\t\t\tsource_pidib\t\t\t = advect & (config::G_PARTICLE_NUM_PER_BLOCK - 1);\n\t\t\tadvection_source_blockno = prev_partition.bin_offsets[advection_source_blockno] + source_pidib / config::G_BIN_CAPACITY;\n\t\t}\n\t\tvec3 pos;\n\t\t{\n\t\t\tauto source_particle_bin = particle_buffer.ch(_0, advection_source_blockno);\n\t\t\tpos[0]\t\t\t\t\t = source_particle_bin.val(_0, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tpos[1]\t\t\t\t\t = source_particle_bin.val(_1, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tpos[2]\t\t\t\t\t = source_particle_bin.val(_2, source_pidib % config::G_BIN_CAPACITY);\n\t\t}\n\t\tivec3 local_base_index = (pos * config::G_DX_INV + 0.5f).cast() - 1;\n\t\tvec3 local_pos\t\t = pos - local_base_index * config::G_DX;\n\t\tbase_index\t\t\t = local_base_index;\n\n\t\tvec3x3 dws;\n#pragma unroll 3\n\t\tfor(int dd = 0; dd < 3; ++dd) {\n\t\t\tfloat d\t = (local_pos[dd] - static_cast(std::floor(local_pos[dd] * config::G_DX_INV + 0.5f) - 1) * config::G_DX) * config::G_DX_INV;\n\t\t\tdws(dd, 0) = 0.5f * (1.5f - d) * (1.5f - d);\n\t\t\td -= 1.0f;\n\t\t\tdws(dd, 1)\t\t\t = 0.75f - d * d;\n\t\t\td\t\t\t\t\t = 0.5f + d;\n\t\t\tdws(dd, 2)\t\t\t = 0.5f * d * d;\n\t\t\tlocal_base_index[dd] = ((local_base_index[dd] - 1) & config::G_BLOCKMASK) + 1;\n\t\t}\n\t\tvec3 vel;\n\t\tvel.set(0.f);\n\t\tvec9 C;\n\t\tC.set(0.f);\n#pragma unroll 3\n\t\tfor(char i = 0; i < 3; i++) {\n#pragma unroll 3\n\t\t\tfor(char j = 0; j < 3; j++) {\n#pragma unroll 3\n\t\t\t\tfor(char k = 0; k < 3; k++) {\n\t\t\t\t\tvec3 xixp = vec3 {static_cast(i), static_cast(j), static_cast(k)} * config::G_DX - local_pos;\n\t\t\t\t\tfloat W\t = dws(0, i) * dws(1, j) * dws(2, k);\n\t\t\t\t\tvec3 vi {g2pbuffer[0][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], g2pbuffer[1][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], g2pbuffer[2][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)]};\n\t\t\t\t\tvel += vi * W;\n\t\t\t\t\tC[0] += W * vi[0] * xixp[0];\n\t\t\t\t\tC[1] += W * vi[1] * xixp[0];\n\t\t\t\t\tC[2] += W * vi[2] * xixp[0];\n\t\t\t\t\tC[3] += W * vi[0] * xixp[1];\n\t\t\t\t\tC[4] += W * vi[1] * xixp[1];\n\t\t\t\t\tC[5] += W * vi[2] * xixp[1];\n\t\t\t\t\tC[6] += W * vi[0] * xixp[2];\n\t\t\t\t\tC[7] += W * vi[1] * xixp[2];\n\t\t\t\t\tC[8] += W * vi[2] * xixp[2];\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\tpos += vel * dt;\n\n#pragma unroll 9\n\t\tfor(int d = 0; d < 9; ++d) {\n\t\t\tdws.val(d) = C[d] * dt * config::G_D_INV + ((d & 0x3) ? 0.f : 1.f);\n\t\t}\n\n\t\tvec9 contrib;\n\t\t{\n\t\t\tvec9 F;\n\t\t\tfloat log_jp;\n\t\t\tauto source_particle_bin = particle_buffer.ch(_0, advection_source_blockno);\n\t\t\tcontrib[0]\t\t\t\t = source_particle_bin.val(_3, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[1]\t\t\t\t = source_particle_bin.val(_4, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[2]\t\t\t\t = source_particle_bin.val(_5, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[3]\t\t\t\t = source_particle_bin.val(_6, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[4]\t\t\t\t = source_particle_bin.val(_7, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[5]\t\t\t\t = source_particle_bin.val(_8, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[6]\t\t\t\t = source_particle_bin.val(_9, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[7]\t\t\t\t = source_particle_bin.val(_10, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[8]\t\t\t\t = source_particle_bin.val(_11, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tlog_jp\t\t\t\t\t = source_particle_bin.val(_12, source_pidib % config::G_BIN_CAPACITY);\n\n\t\t\tmatrix_matrix_multiplication_3d(dws.data_arr(), contrib.data_arr(), F.data_arr());\n\t\t\tcompute_stress_sand(particle_buffer.volume, particle_buffer.mu, particle_buffer.lambda, particle_buffer.cohesion, particle_buffer.beta, particle_buffer.yield_surface, particle_buffer.volume_correction, log_jp, F, contrib);\n\t\t\t{\n\t\t\t\tauto particle_bin\t\t\t\t\t\t\t\t\t\t\t\t\t = next_particle_buffer.ch(_0, partition.bin_offsets[src_blockno] + particle_id_in_block / config::G_BIN_CAPACITY);\n\t\t\t\tparticle_bin.val(_0, particle_id_in_block % config::G_BIN_CAPACITY)\t = pos[0];\n\t\t\t\tparticle_bin.val(_1, particle_id_in_block % config::G_BIN_CAPACITY)\t = pos[1];\n\t\t\t\tparticle_bin.val(_2, particle_id_in_block % config::G_BIN_CAPACITY)\t = pos[2];\n\t\t\t\tparticle_bin.val(_3, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[0];\n\t\t\t\tparticle_bin.val(_4, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[1];\n\t\t\t\tparticle_bin.val(_5, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[2];\n\t\t\t\tparticle_bin.val(_6, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[3];\n\t\t\t\tparticle_bin.val(_7, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[4];\n\t\t\t\tparticle_bin.val(_8, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[5];\n\t\t\t\tparticle_bin.val(_9, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[6];\n\t\t\t\tparticle_bin.val(_10, particle_id_in_block % config::G_BIN_CAPACITY) = F[7];\n\t\t\t\tparticle_bin.val(_11, particle_id_in_block % config::G_BIN_CAPACITY) = F[8];\n\t\t\t\tparticle_bin.val(_12, particle_id_in_block % config::G_BIN_CAPACITY) = log_jp;\n\t\t\t}\n\n\t\t\tcontrib = (C * particle_buffer.mass - contrib * new_dt) * config::G_D_INV;\n\t\t}\n\n\t\tlocal_base_index = (pos * config::G_DX_INV + 0.5f).cast() - 1;\n\t\t{\n\t\t\tint dirtag = dir_offset((base_index - 1) / static_cast(config::G_BLOCKSIZE) - (local_base_index - 1) / static_cast(config::G_BLOCKSIZE));\n\t\t\tpartition.add_advection(local_base_index - 1, dirtag, particle_id_in_block);\n\t\t}\n\t\t// dws[d] = bspline_weight(local_pos[d]);\n\n#pragma unroll 3\n\t\tfor(char dd = 0; dd < 3; ++dd) {\n\t\t\tlocal_pos[dd] = pos[dd] - static_cast(local_base_index[dd]) * config::G_DX;\n\t\t\tfloat d\t\t = (local_pos[dd] - static_cast(std::floor(local_pos[dd] * config::G_DX_INV + 0.5f) - 1) * config::G_DX) * config::G_DX_INV;\n\t\t\tdws(dd, 0)\t = 0.5f * (1.5f - d) * (1.5f - d);\n\t\t\td -= 1.0f;\n\t\t\tdws(dd, 1) = 0.75f - d * d;\n\t\t\td\t\t = 0.5f + d;\n\t\t\tdws(dd, 2) = 0.5f * d * d;\n\n\t\t\tlocal_base_index[dd] = (((base_index[dd] - 1) & config::G_BLOCKMASK) + 1) + local_base_index[dd] - base_index[dd];\n\t\t}\n#pragma unroll 3\n\t\tfor(char i = 0; i < 3; i++) {\n#pragma unroll 3\n\t\t\tfor(char j = 0; j < 3; j++) {\n#pragma unroll 3\n\t\t\t\tfor(char k = 0; k < 3; k++) {\n\t\t\t\t\tpos\t\t= vec3 {static_cast(i), static_cast(j), static_cast(k)} * config::G_DX - local_pos;\n\t\t\t\t\tfloat W = dws(0, i) * dws(1, j) * dws(2, k);\n\t\t\t\t\tauto wm = particle_buffer.mass * W;\n\t\t\t\t\tatomicAdd(&p2gbuffer[0][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], wm);\n\t\t\t\t\tatomicAdd(&p2gbuffer[1][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], wm * vel[0] + (contrib[0] * pos[0] + contrib[3] * pos[1] + contrib[6] * pos[2]) * W);\n\t\t\t\t\tatomicAdd(&p2gbuffer[2][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], wm * vel[1] + (contrib[1] * pos[0] + contrib[4] * pos[1] + contrib[7] * pos[2]) * W);\n\t\t\t\t\tatomicAdd(&p2gbuffer[3][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], wm * vel[2] + (contrib[2] * pos[0] + contrib[5] * pos[1] + contrib[8] * pos[2]) * W);\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\t__syncthreads();\n\t/// arena no, channel no, cell no\n\tfor(int base = static_cast(threadIdx.x); base < NUM_M_VI_IN_ARENA; base += static_cast(blockDim.x)) {\n\t\tchar local_block_id = static_cast(base / NUM_M_VI_PER_BLOCK);\n\t\tauto blockno\t\t= partition.query(ivec3 {blockid[0] + ((local_block_id & 4) != 0 ? 1 : 0), blockid[1] + ((local_block_id & 2) != 0 ? 1 : 0), blockid[2] + ((local_block_id & 1) != 0 ? 1 : 0)});\n\t\t// auto grid_block = next_grid.template ch<0>(blockno);\n\t\tint channelid = static_cast(base & (NUM_M_VI_PER_BLOCK - 1));\n\t\tchar c\t\t = static_cast(channelid % config::G_BLOCKVOLUME);\n\n\t\tchar cz = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tchar cy = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tchar cx = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tfloat val = p2gbuffer[channelid][static_cast(static_cast(cx) + (local_block_id & 4 ? config::G_BLOCKSIZE : 0))][static_cast(static_cast(cy) + (local_block_id & 2 ? config::G_BLOCKSIZE : 0))][static_cast(static_cast(cz) + (local_block_id & 1 ? config::G_BLOCKSIZE : 0))];\n\t\tif(channelid == 0) {\n\t\t\tatomicAdd(&next_grid.ch(_0, blockno).val_1d(_0, c), val);\n\t\t} else if(channelid == 1) {\n\t\t\tatomicAdd(&next_grid.ch(_0, blockno).val_1d(_1, c), val);\n\t\t} else if(channelid == 2) {\n\t\t\tatomicAdd(&next_grid.ch(_0, blockno).val_1d(_2, c), val);\n\t\t} else {\n\t\t\tatomicAdd(&next_grid.ch(_0, blockno).val_1d(_3, c), val);\n\t\t}\n\t}\n}\n\ntemplate\n__global__ void g2p2g(float dt, float new_dt, const ivec3* __restrict__ blocks, const ParticleBuffer particle_buffer, ParticleBuffer next_particle_buffer, const Partition prev_partition, Partition partition, const Grid grid, Grid next_grid) {\n\tstatic constexpr uint64_t NUM_VI_PER_BLOCK = static_cast(config::G_BLOCKVOLUME) * 3;\n\tstatic constexpr uint64_t NUM_VI_IN_ARENA = NUM_VI_PER_BLOCK << 3;\n\n\tstatic constexpr uint64_t NUM_M_VI_PER_BLOCK = static_cast(config::G_BLOCKVOLUME) * 4;\n\tstatic constexpr uint64_t NUM_M_VI_IN_ARENA\t = NUM_M_VI_PER_BLOCK << 3;\n\n\tstatic constexpr unsigned ARENAMASK = (config::G_BLOCKSIZE << 1) - 1;\n\tstatic constexpr unsigned ARENABITS = config::G_BLOCKBITS + 1;\n\n\tusing ViArena\t = std::array, config::G_BLOCKSIZE << 1>, config::G_BLOCKSIZE << 1>, 3>*;\n\tusing ViArenaRef = std::array, config::G_BLOCKSIZE << 1>, config::G_BLOCKSIZE << 1>, 3>&;\n\tusing MViArena\t = std::array, config::G_BLOCKSIZE << 1>, config::G_BLOCKSIZE << 1>, 4>*;\n\tusing MViArenaRef = std::array, config::G_BLOCKSIZE << 1>, config::G_BLOCKSIZE << 1>, 4>&;\n\n\textern __shared__ char shmem[];//NOLINT(modernize-avoid-c-arrays, readability-redundant-declaration) Cannot declare runtime size shared memory as std::array; extern has different meaning here\n\n\tViArenaRef __restrict__ g2pbuffer = *static_cast(static_cast(static_cast(shmem)));\n\tMViArenaRef __restrict__ p2gbuffer = *static_cast(static_cast(static_cast(shmem) + NUM_VI_IN_ARENA * sizeof(float)));\n\n\tivec3 blockid;\n\tint src_blockno;\n\tif(blocks != nullptr) {\n\t\tblockid\t\t= blocks[blockIdx.x];\n\t\tsrc_blockno = partition.query(blockid);\n\t} else {\n\t\tif(partition.halo_marks[blockIdx.x]) {\n\t\t\treturn;\n\t\t}\n\t\tblockid = partition.active_keys[blockIdx.x];\n\n\t\tint src_blockno\t\t\t = static_cast(blockIdx.x);\n\t\tint particle_bucket_size = next_particle_buffer.particle_bucket_sizes[src_blockno];\n\t\tif(particle_bucket_size == 0) {\n\t\t\treturn;\n\t\t}\n\t}\n\n\tfor(int base = static_cast(threadIdx.x); base < NUM_VI_IN_ARENA; base += static_cast(blockDim.x)) {\n\t\tchar local_block_id = static_cast(base / NUM_VI_PER_BLOCK);\n\t\tauto blockno\t\t= partition.query(ivec3 {blockid[0] + ((local_block_id & 4) != 0 ? 1 : 0), blockid[1] + ((local_block_id & 2) != 0 ? 1 : 0), blockid[2] + ((local_block_id & 1) != 0 ? 1 : 0)});\n\t\tauto grid_block\t\t= grid.ch(_0, blockno);\n\t\tint channelid\t\t= static_cast(base % NUM_VI_PER_BLOCK);\n\t\tchar c\t\t\t\t= static_cast(channelid & 0x3f);\n\n\t\tchar cz = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tchar cy = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tchar cx = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tfloat val;\n\t\tif(channelid == 0) {\n\t\t\tval = grid_block.val_1d(_1, c);\n\t\t} else if(channelid == 1) {\n\t\t\tval = grid_block.val_1d(_2, c);\n\t\t} else {\n\t\t\tval = grid_block.val_1d(_3, c);\n\t\t}\n\t\tg2pbuffer[channelid][static_cast(static_cast(cx) + (local_block_id & 4 ? config::G_BLOCKSIZE : 0))][static_cast(static_cast(cy) + (local_block_id & 2 ? config::G_BLOCKSIZE : 0))][static_cast(static_cast(cz) + (local_block_id & 1 ? config::G_BLOCKSIZE : 0))] = val;\n\t}\n\t__syncthreads();\n\tfor(int base = static_cast(threadIdx.x); base < NUM_M_VI_IN_ARENA; base += static_cast(blockDim.x)) {\n\t\tint loc = static_cast(base);\n\t\tchar z\t= static_cast(loc & ARENAMASK);\n\t\tloc >>= ARENABITS;\n\n\t\tchar y = static_cast(loc & ARENAMASK);\n\t\tloc >>= ARENABITS;\n\n\t\tchar x\t\t\t\t\t\t\t\t = static_cast(loc & ARENAMASK);\n\t\tp2gbuffer[loc >> ARENABITS][x][y][z] = 0.0f;\n\t}\n\t__syncthreads();\n\n\tfor(int particle_id_in_block = static_cast(threadIdx.x); particle_id_in_block < partition.particle_bucket_sizes[src_blockno]; particle_id_in_block += static_cast(blockDim.x)) {\n\t\tint advection_source_blockno;\n\t\tint source_pidib;\n\t\tivec3 base_index;\n\t\t{\n\t\t\tint advect = partition.blockbuckets[src_blockno * config::G_PARTICLE_NUM_PER_BLOCK + particle_id_in_block];\n\t\t\tdir_components(advect / config::G_PARTICLE_NUM_PER_BLOCK, base_index);\n\t\t\tbase_index += blockid;\n\t\t\tadvection_source_blockno = prev_partition.query(base_index);\n\t\t\tsource_pidib\t\t\t = advect & (config::G_PARTICLE_NUM_PER_BLOCK - 1);\n\t\t\tadvection_source_blockno = prev_partition.bin_offsets[advection_source_blockno] + source_pidib / config::G_BIN_CAPACITY;\n\t\t}\n\t\tvec3 pos;\n\t\t{\n\t\t\tauto source_particle_bin = particle_buffer.ch(_0, advection_source_blockno);\n\t\t\tpos[0]\t\t\t\t\t = source_particle_bin.val(_0, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tpos[1]\t\t\t\t\t = source_particle_bin.val(_1, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tpos[2]\t\t\t\t\t = source_particle_bin.val(_2, source_pidib % config::G_BIN_CAPACITY);\n\t\t}\n\t\tivec3 local_base_index = (pos * config::G_DX_INV + 0.5f).cast() - 1;\n\t\tvec3 local_pos\t\t = pos - local_base_index * config::G_DX;\n\t\tbase_index\t\t\t = local_base_index;\n\n\t\tvec3x3 dws;\n#pragma unroll 3\n\t\tfor(int dd = 0; dd < 3; ++dd) {\n\t\t\tfloat d\t = (local_pos[dd] - static_cast(std::floor(local_pos[dd] * config::G_DX_INV + 0.5f) - 1) * config::G_DX) * config::G_DX_INV;\n\t\t\tdws(dd, 0) = 0.5f * (1.5f - d) * (1.5f - d);\n\t\t\td -= 1.0f;\n\t\t\tdws(dd, 1)\t\t\t = 0.75f - d * d;\n\t\t\td\t\t\t\t\t = 0.5f + d;\n\t\t\tdws(dd, 2)\t\t\t = 0.5f * d * d;\n\t\t\tlocal_base_index[dd] = ((local_base_index[dd] - 1) & config::G_BLOCKMASK) + 1;\n\t\t}\n\t\tvec3 vel;\n\t\tvel.set(0.f);\n\t\tvec9 C;\n\t\tC.set(0.f);\n#pragma unroll 3\n\t\tfor(char i = 0; i < 3; i++) {\n#pragma unroll 3\n\t\t\tfor(char j = 0; j < 3; j++) {\n#pragma unroll 3\n\t\t\t\tfor(char k = 0; k < 3; k++) {\n\t\t\t\t\tvec3 xixp = vec3 {static_cast(i), static_cast(j), static_cast(k)} * config::G_DX - local_pos;\n\t\t\t\t\tfloat W\t = dws(0, i) * dws(1, j) * dws(2, k);\n\t\t\t\t\tvec3 vi {g2pbuffer[0][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], g2pbuffer[1][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], g2pbuffer[2][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)]};\n\t\t\t\t\tvel += vi * W;\n\t\t\t\t\tC[0] += W * vi[0] * xixp[0];\n\t\t\t\t\tC[1] += W * vi[1] * xixp[0];\n\t\t\t\t\tC[2] += W * vi[2] * xixp[0];\n\t\t\t\t\tC[3] += W * vi[0] * xixp[1];\n\t\t\t\t\tC[4] += W * vi[1] * xixp[1];\n\t\t\t\t\tC[5] += W * vi[2] * xixp[1];\n\t\t\t\t\tC[6] += W * vi[0] * xixp[2];\n\t\t\t\t\tC[7] += W * vi[1] * xixp[2];\n\t\t\t\t\tC[8] += W * vi[2] * xixp[2];\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\tpos += vel * dt;\n\n#pragma unroll 9\n\t\tfor(int d = 0; d < 9; ++d) {\n\t\t\tdws.val(d) = C[d] * dt * config::G_D_INV + ((d & 0x3) ? 0.f : 1.f);\n\t\t}\n\n\t\tvec9 contrib;\n\t\t{\n\t\t\tvec9 F;\n\t\t\tfloat log_jp;\n\t\t\tauto source_particle_bin = particle_buffer.ch(_0, advection_source_blockno);\n\t\t\tcontrib[0]\t\t\t\t = source_particle_bin.val(_3, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[1]\t\t\t\t = source_particle_bin.val(_4, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[2]\t\t\t\t = source_particle_bin.val(_5, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[3]\t\t\t\t = source_particle_bin.val(_6, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[4]\t\t\t\t = source_particle_bin.val(_7, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[5]\t\t\t\t = source_particle_bin.val(_8, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[6]\t\t\t\t = source_particle_bin.val(_9, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[7]\t\t\t\t = source_particle_bin.val(_10, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tcontrib[8]\t\t\t\t = source_particle_bin.val(_11, source_pidib % config::G_BIN_CAPACITY);\n\t\t\tlog_jp\t\t\t\t\t = source_particle_bin.val(_12, source_pidib % config::G_BIN_CAPACITY);\n\n\t\t\tmatrix_matrix_multiplication_3d(dws.data_arr(), contrib.data_arr(), F.data_arr());\n\t\t\tcompute_stress_nacc(particle_buffer.volume, particle_buffer.mu, particle_buffer.lambda, particle_buffer.bm, particle_buffer.xi, particle_buffer.beta, particle_buffer.msqr, particle_buffer.hardening_on, log_jp, F, contrib);\n\t\t\t{\n\t\t\t\tauto particle_bin\t\t\t\t\t\t\t\t\t\t\t\t\t = next_particle_buffer.ch(_0, partition.bin_offsets[src_blockno] + particle_id_in_block / config::G_BIN_CAPACITY);\n\t\t\t\tparticle_bin.val(_0, particle_id_in_block % config::G_BIN_CAPACITY)\t = pos[0];\n\t\t\t\tparticle_bin.val(_1, particle_id_in_block % config::G_BIN_CAPACITY)\t = pos[1];\n\t\t\t\tparticle_bin.val(_2, particle_id_in_block % config::G_BIN_CAPACITY)\t = pos[2];\n\t\t\t\tparticle_bin.val(_3, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[0];\n\t\t\t\tparticle_bin.val(_4, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[1];\n\t\t\t\tparticle_bin.val(_5, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[2];\n\t\t\t\tparticle_bin.val(_6, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[3];\n\t\t\t\tparticle_bin.val(_7, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[4];\n\t\t\t\tparticle_bin.val(_8, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[5];\n\t\t\t\tparticle_bin.val(_9, particle_id_in_block % config::G_BIN_CAPACITY)\t = F[6];\n\t\t\t\tparticle_bin.val(_10, particle_id_in_block % config::G_BIN_CAPACITY) = F[7];\n\t\t\t\tparticle_bin.val(_11, particle_id_in_block % config::G_BIN_CAPACITY) = F[8];\n\t\t\t\tparticle_bin.val(_12, particle_id_in_block % config::G_BIN_CAPACITY) = log_jp;\n\t\t\t}\n\n\t\t\tcontrib = (C * particle_buffer.mass - contrib * new_dt) * config::G_D_INV;\n\t\t}\n\n\t\tlocal_base_index = (pos * config::G_DX_INV + 0.5f).cast() - 1;\n\t\t{\n\t\t\tint dirtag = dir_offset((base_index - 1) / static_cast(config::G_BLOCKSIZE) - (local_base_index - 1) / static_cast(config::G_BLOCKSIZE));\n\t\t\tpartition.add_advection(local_base_index - 1, dirtag, particle_id_in_block);\n\t\t}\n\t\t// dws[d] = bspline_weight(local_pos[d]);\n\n#pragma unroll 3\n\t\tfor(char dd = 0; dd < 3; ++dd) {\n\t\t\tlocal_pos[dd] = pos[dd] - static_cast(local_base_index[dd]) * config::G_DX;\n\t\t\tfloat d\t\t = (local_pos[dd] - static_cast(std::floor(local_pos[dd] * config::G_DX_INV + 0.5f) - 1) * config::G_DX) * config::G_DX_INV;\n\t\t\tdws(dd, 0)\t = 0.5f * (1.5f - d) * (1.5f - d);\n\t\t\td -= 1.0f;\n\t\t\tdws(dd, 1) = 0.75f - d * d;\n\t\t\td\t\t = 0.5f + d;\n\t\t\tdws(dd, 2) = 0.5f * d * d;\n\n\t\t\tlocal_base_index[dd] = (((base_index[dd] - 1) & config::G_BLOCKMASK) + 1) + local_base_index[dd] - base_index[dd];\n\t\t}\n#pragma unroll 3\n\t\tfor(char i = 0; i < 3; i++) {\n#pragma unroll 3\n\t\t\tfor(char j = 0; j < 3; j++) {\n#pragma unroll 3\n\t\t\t\tfor(char k = 0; k < 3; k++) {\n\t\t\t\t\tpos\t\t= vec3 {static_cast(i), static_cast(j), static_cast(k)} * config::G_DX - local_pos;\n\t\t\t\t\tfloat W = dws(0, i) * dws(1, j) * dws(2, k);\n\t\t\t\t\tauto wm = particle_buffer.mass * W;\n\t\t\t\t\tatomicAdd(&p2gbuffer[0][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], wm);\n\t\t\t\t\tatomicAdd(&p2gbuffer[1][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], wm * vel[0] + (contrib[0] * pos[0] + contrib[3] * pos[1] + contrib[6] * pos[2]) * W);\n\t\t\t\t\tatomicAdd(&p2gbuffer[2][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], wm * vel[1] + (contrib[1] * pos[0] + contrib[4] * pos[1] + contrib[7] * pos[2]) * W);\n\t\t\t\t\tatomicAdd(&p2gbuffer[3][static_cast(static_cast(local_base_index[0]) + i)][static_cast(static_cast(local_base_index[1]) + j)][static_cast(static_cast(local_base_index[2]) + k)], wm * vel[2] + (contrib[2] * pos[0] + contrib[5] * pos[1] + contrib[8] * pos[2]) * W);\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n\t__syncthreads();\n\t/// arena no, channel no, cell no\n\tfor(int base = static_cast(threadIdx.x); base < NUM_M_VI_IN_ARENA; base += static_cast(blockDim.x)) {\n\t\tchar local_block_id = static_cast(base / NUM_M_VI_PER_BLOCK);\n\t\tauto blockno\t\t= partition.query(ivec3 {blockid[0] + ((local_block_id & 4) != 0 ? 1 : 0), blockid[1] + ((local_block_id & 2) != 0 ? 1 : 0), blockid[2] + ((local_block_id & 1) != 0 ? 1 : 0)});\n\t\t// auto grid_block = next_grid.template ch<0>(blockno);\n\t\tint channelid = static_cast(base & (NUM_M_VI_PER_BLOCK - 1));\n\t\tchar c\t\t = static_cast(channelid % config::G_BLOCKVOLUME);\n\n\t\tchar cz = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tchar cy = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tchar cx = static_cast(channelid & config::G_BLOCKMASK);\n\t\tchannelid >>= config::G_BLOCKBITS;\n\n\t\tfloat val = p2gbuffer[channelid][static_cast(static_cast(cx) + (local_block_id & 4 ? config::G_BLOCKSIZE : 0))][static_cast(static_cast(cy) + (local_block_id & 2 ? config::G_BLOCKSIZE : 0))][static_cast(static_cast(cz) + (local_block_id & 1 ? config::G_BLOCKSIZE : 0))];\n\t\tif(channelid == 0) {\n\t\t\tatomicAdd(&next_grid.ch(_0, blockno).val_1d(_0, c), val);\n\t\t} else if(channelid == 1) {\n\t\t\tatomicAdd(&next_grid.ch(_0, blockno).val_1d(_1, c), val);\n\t\t} else if(channelid == 2) {\n\t\t\tatomicAdd(&next_grid.ch(_0, blockno).val_1d(_2, c), val);\n\t\t} else {\n\t\t\tatomicAdd(&next_grid.ch(_0, blockno).val_1d(_3, c), val);\n\t\t}\n\t}\n}\n\ntemplate\n__global__ void mark_active_grid_blocks(uint32_t block_count, const Grid grid, int* marks) {\n\tauto idx\t= blockIdx.x * blockDim.x + threadIdx.x;\n\tint blockno = static_cast(idx / config::G_BLOCKVOLUME);\n\tint cellno\t= static_cast(idx % config::G_BLOCKVOLUME);\n\tif(blockno >= block_count) {\n\t\treturn;\n\t}\n\tif(grid.ch(_0, blockno).val_1d(_0, cellno) != 0.f) {\n\t\tmarks[blockno] = 1;\n\t}\n}\n\n__global__ void mark_active_particle_blocks(uint32_t block_count, const int* __restrict__ particle_bucket_sizes, int* marks) {\n\tconst std::size_t blockno = static_cast(blockIdx.x) * blockDim.x + threadIdx.x;\n\tif(blockno >= block_count) {\n\t\treturn;\n\t}\n\tmarks[blockno] = particle_bucket_sizes[blockno] > 0 ? 1 : 0;\n}\n\ntemplate\n__global__ void update_partition(uint32_t block_count, const int* __restrict__ source_nos, const Partition partition, Partition next_partition) {\n\t__shared__ std::size_t source_no[1];//NOLINT(modernize-avoid-c-arrays) Cannot declare shared memory as std::array?\n\tstd::size_t blockno = blockIdx.x;\n\tif(blockno >= block_count) {\n\t\treturn;\n\t}\n\tif(threadIdx.x == 0) {\n\t\tsource_no[0]\t\t\t\t\t\t= source_nos[blockno];\n\t\tauto source_blockid\t\t\t\t\t= partition.active_keys[source_no[0]];\n\t\tnext_partition.active_keys[blockno] = source_blockid;\n\t\tnext_partition.reinsert(static_cast(blockno));\n\t\tnext_partition.particle_bucket_sizes[blockno] = partition.particle_bucket_sizes[source_no[0]];\n\t}\n\t__syncthreads();\n\n\tauto particle_counts = next_partition.particle_bucket_sizes[blockno];\n\tfor(int particle_id_in_block = static_cast(threadIdx.x); particle_id_in_block < particle_counts; particle_id_in_block += static_cast(blockDim.x)) {\n\t\tnext_partition.blockbuckets[blockno * config::G_PARTICLE_NUM_PER_BLOCK + particle_id_in_block] = partition.blockbuckets[source_no[0] * config::G_PARTICLE_NUM_PER_BLOCK + particle_id_in_block];\n\t}\n}\n\ntemplate\n__global__ void copy_selected_grid_blocks(const ivec3* __restrict__ prev_blockids, const Partition partition, const int* __restrict__ marks, Grid prev_grid, Grid grid) {\n\tauto blockid = prev_blockids[blockIdx.x];\n\tif(marks[blockIdx.x]) {\n\t\tauto blockno = partition.query(blockid);\n\t\tif(blockno == -1) {\n\t\t\treturn;\n\t\t}\n\t\tauto sourceblock\t\t\t\t\t= prev_grid.ch(_0, blockIdx.x);\n\t\tauto targetblock\t\t\t\t\t= grid.ch(_0, blockno);\n\t\ttargetblock.val_1d(_0, threadIdx.x) = sourceblock.val_1d(_0, threadIdx.x);\n\t\ttargetblock.val_1d(_1, threadIdx.x) = sourceblock.val_1d(_1, threadIdx.x);\n\t\ttargetblock.val_1d(_2, threadIdx.x) = sourceblock.val_1d(_2, threadIdx.x);\n\t\ttargetblock.val_1d(_3, threadIdx.x) = sourceblock.val_1d(_3, threadIdx.x);\n\t}\n}\n\ntemplate\n__global__ void check_table(uint32_t block_count, Partition partition) {\n\tuint32_t blockno = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(blockno >= block_count) {\n\t\treturn;\n\t}\n\tauto blockid = partition.active_keys[blockno];\n\tif(partition.query(blockid) != blockno)\n\t\tprintf(\"FUCK, partition table is wrong!\\n\");\n}\n\ntemplate\n__global__ void sum_grid_mass(Grid grid, float* sum) {\n\tatomicAdd(sum, grid.ch(_0, blockIdx.x).val_1d(_0, threadIdx.x));\n}\n\n__global__ void sum_particle_counts(uint32_t count, int* __restrict__ counts, int* sum) {\n\tauto idx = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(idx >= count) {\n\t\treturn;\n\t}\n\tatomicAdd(sum, counts[idx]);\n}\n\ntemplate\n__global__ void check_partition(uint32_t block_count, Partition partition) {\n\tint idx = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(idx >= block_count) {\n\t\treturn;\n\t}\n\tivec3 blockid = partition.active_keys[idx];\n\tif(blockid[0] == 0 || blockid[1] == 0 || blockid[2] == 0) {\n\t\tprintf(\"\\tDAMN, encountered zero block record\\n\");\n\t}\n\tif(partition.query(blockid) != idx) {\n\t\tint id\t = partition.query(blockid);\n\t\tivec3 bid = partition.active_keys[id];\n\t\tprintf(\n\t\t\t\"\\t\\tcheck partition %d, (%d, %d, %d), feedback index %d, (%d, %d, \"\n\t\t\t\"%d)\\n\",\n\t\t\tidx,\n\t\t\t(int) blockid[0],\n\t\t\t(int) blockid[1],\n\t\t\t(int) blockid[2],\n\t\t\tid,\n\t\t\tbid[0],\n\t\t\tbid[1],\n\t\t\tbid[2]\n\t\t);\n\t}\n}\n\ntemplate\n__global__ void check_partition_domain(uint32_t block_count, int did, Domain const domain, Partition partition) {\n\tint idx = blockIdx.x * blockDim.x + threadIdx.x;\n\tif(idx >= block_count) {\n\t\treturn;\n\t}\n\tivec3 blockid = partition.active_keys[idx];\n\tif(domain.inside(blockid)) {\n\t\tprintf(\"%d-th block (%d, %d, %d) is in domain[%d] (%d, %d, %d)-(%d, %d, %d)\\n\", idx, blockid[0], blockid[1], blockid[2], did, domain._min[0], domain._min[1], domain._min[2], domain._max[0], domain._max[1], domain._max[2]);\n\t}\n}\n\ntemplate\n__global__ void retrieve_particle_buffer(Partition partition, Partition prev_partition, ParticleBuffer particle_buffer, ParticleArray particle_array, int* parcount) {\n\tint particle_counts\t = partition.particle_bucket_sizes[blockIdx.x];\n\tivec3 blockid\t\t = partition.active_keys[blockIdx.x];\n\tauto advection_bucket = partition.blockbuckets + blockIdx.x * config::G_PARTICLE_NUM_PER_BLOCK;\n\t// auto particle_offset = partition.bin_offsets[blockIdx.x];\n\tfor(int particle_id_in_block = static_cast(threadIdx.x); particle_id_in_block < particle_counts; particle_id_in_block += static_cast(blockDim.x)) {\n\t\tauto advect = advection_bucket[particle_id_in_block];\n\t\tivec3 source_blockid;\n\t\tdir_components(advect / config::G_PARTICLE_NUM_PER_BLOCK, source_blockid);\n\t\tsource_blockid += blockid;\n\t\tauto advection_source_blockno = prev_partition.query(source_blockid);\n\t\tauto source_pidib\t\t\t = advect % config::G_PARTICLE_NUM_PER_BLOCK;\n\t\tauto source_bin\t\t\t\t = particle_buffer.ch(_0, prev_partition.bin_offsets[advection_source_blockno] + source_pidib / config::G_BIN_CAPACITY);\n\t\tauto _source_pidib\t\t\t = source_pidib % config::G_BIN_CAPACITY;\n\n\t\tauto particle_id = atomicAdd(parcount, 1);\n\t\t/// pos\n\t\tparticle_array.val(_0, particle_id) = source_bin.val(_0, _source_pidib);\n\t\tparticle_array.val(_1, particle_id) = source_bin.val(_1, _source_pidib);\n\t\tparticle_array.val(_2, particle_id) = source_bin.val(_2, _source_pidib);\n\t}\n}\n//NOLINTEND(cppcoreguidelines-pro-bounds-pointer-arithmetic, readability-magic-numbers, readability-identifier-naming, misc-definitions-in-headers)\n}// namespace mn\n\n#endif" }, { "path": "Projects/MGSP/mgsp.cu", "content": "#include \n#include \n#include \n#include \n\n#include \n\n#include \"mgsp_benchmark.cuh\"\n#include \"partition_domain.h\"\n\n// dragon_particles.bin, 775196\n// cube256_2.bin, 1048576\n// two_dragons.bin, 388950\n\nconstexpr size_t DRAGON_PARTICLES_SIZE = 775196;\nconstexpr size_t CUBE_256_2_SIZE\t = 1048576;\nconstexpr size_t TWO_DRAGONS_SIZE\t = 388950;\n\nconstexpr size_t SCENARIO = 3;\n\ndecltype(auto) load_model(std::size_t particle_counts, const std::string& filename) {\n\tstd::vector> rawpos(particle_counts);\n\tauto addr_str = std::string(AssetDirPath) + \"MpmParticles/\";\n\tFILE* f;\n\tfopen_s(&f, (addr_str + filename).c_str(), \"rb\");\n\tstd::fread(rawpos.data(), sizeof(float), rawpos.size() * mn::config::NUM_DIMENSIONS, f);\n\tstd::fclose(f);\n\treturn rawpos;\n}\n\n//NOLINTBEGIN(readability-magic-numbers) Numbers are scenario parameters\n// load from analytic levelset\n// init models\nvoid init_models(std::array>, mn::config::G_DEVICE_COUNT> models, int opt = 0) {\n\t(void) DRAGON_PARTICLES_SIZE;\n\t(void) CUBE_256_2_SIZE;\n\t(void) TWO_DRAGONS_SIZE;\n\tswitch(opt) {\n\t\tcase 0:\n\t\t\tmodels[0] = load_model(DRAGON_PARTICLES_SIZE, \"dragon_particles.bin\");\n\t\t\tmodels[1] = read_sdf(std::string {\"two_dragons.sdf\"}, 8.f, mn::config::G_DX, mn::vec {0.5f, 0.5f, 0.5f}, mn::vec {0.2f, 0.2f, 0.2f});\n\t\t\tbreak;\n\t\tcase 1:\n\t\t\tmodels[0] = load_model(DRAGON_PARTICLES_SIZE, \"dragon_particles.bin\");\n\t\t\tmodels[1] = load_model(DRAGON_PARTICLES_SIZE, \"dragon_particles.bin\");\n\t\t\tfor(auto& pt: models[1]) {\n\t\t\t\tpt[1] -= 0.3f;\n\t\t\t}\n\t\t\tbreak;\n\t\tcase 2: {\n\t\t\tconstexpr auto LEN\t\t = 54;\n\t\t\tconstexpr auto STRIDE\t = 56;\n\t\t\tconstexpr auto MODEL_COUNT = 1;\n\t\t\tfor(int did = 0; did < mn::config::G_DEVICE_COUNT; ++did) {\n\t\t\t\tmodels[did].clear();\n\t\t\t\tstd::vector> model;\n\t\t\t\tfor(int i = 0; i < MODEL_COUNT; ++i) {\n\t\t\t\t\tauto idx = (did * MODEL_COUNT + i);\n\t\t\t\t\tmodel\t = sample_uniform_box(mn::config::G_DX, mn::ivec3 {18 + ((idx & 1) != 0 ? STRIDE : 0), 18, 18}, mn::ivec3 {18 + ((idx & 1) != 0 ? STRIDE : 0) + LEN, 18 + LEN, 18 + LEN});\n\t\t\t\t\tmodels[did].insert(models[did].end(), model.begin(), model.end());\n\t\t\t\t}\n\t\t\t}\n\t\t} break;\n\t\tcase 3: {\n\t\t\tconstexpr auto LEN\t\t = 72;// 54;\n\t\t\tconstexpr auto STRIDE\t = (mn::config::G_DOMAIN_SIZE / 2);\n\t\t\tconstexpr auto MODEL_COUNT = 1;\n\t\t\tfor(int did = 0; did < mn::config::G_DEVICE_COUNT; ++did) {\n\t\t\t\tmodels[did].clear();\n\t\t\t\tstd::vector> model;\n\t\t\t\tfor(int i = 0; i < MODEL_COUNT; ++i) {\n\t\t\t\t\tauto idx = (did * MODEL_COUNT + i);\n\t\t\t\t\tmodel\t = sample_uniform_box(mn::config::G_DX, mn::ivec3 {18 + ((idx & 1) != 0 ? STRIDE : 0), 18, 18 + ((idx & 2) != 0 ? STRIDE : 0)}, mn::ivec3 {18 + ((idx & 1) != 0 ? STRIDE : 0) + LEN, 18 + LEN / 3, 18 + ((idx & 2) != 0 ? STRIDE : 0) + LEN});\n\t\t\t\t\tmodels[did].insert(models[did].end(), model.begin(), model.end());\n\t\t\t\t}\n\t\t\t}\n\t\t} break;\n\t\tdefault:\n\t\t\tbreak;\n\t}\n}\n//NOLINTEND(readability-magic-numbers)\n\nint main() {\n\tmn::Cuda::startup();\n\n\tstd::array>, mn::config::G_DEVICE_COUNT> models;\n\n\tauto benchmark = std::make_unique();\n\t/// init\n\tinit_models(models, SCENARIO);\n\n\tfor(int did = 0; did < mn::config::G_DEVICE_COUNT; ++did) {\n\t\tbenchmark->init_model(did, models[did]);\n\t}\n\t// benchmark->init_boundary(\"candy_base\");\n\n\tbenchmark->main_loop();\n\t///\n\tmn::IO::flush();\n\tbenchmark.reset();\n\t///\n\tmn::Cuda::shutdown();\n\treturn 0;\n}" }, { "path": "Projects/MGSP/mgsp_benchmark.cuh", "content": "#ifndef MGSP_BENCHMARK_CUH\n#define MGSP_BENCHMARK_CUH\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n\n#include \n#include \n#include \n#include \n#include \n\n#include \"boundary_condition.cuh\"\n#include \"grid_buffer.cuh\"\n#include \"halo_buffer.cuh\"\n#include \"halo_kernels.cuh\"\n#include \"hash_table.cuh\"\n#include \"mgmpm_kernels.cuh\"\n#include \"particle_buffer.cuh\"\n#include \"settings.h\"\n\nnamespace mn {\n\nstruct MgspBenchmark {\n\tstatic constexpr float DEFAULT_DT = 1e-4;\n\tstatic constexpr int DEFAULT_FPS = 24;\n\n\tstatic constexpr size_t BIN_COUNT = 2;\n\n\tusing streamIdx\t\t = Cuda::StreamIndex;\n\tusing eventIdx\t\t = Cuda::EventIndex;\n\tusing host_allocator = HeapAllocator;\n\n\tstruct DeviceAllocator {\t\t\t // hide the global one\n\t\tvoid* allocate(std::size_t bytes) {//NOLINT(readability-convert-member-functions-to-static) Method is designed to be a non-static class member\n\t\t\tvoid* ret = nullptr;\n\t\t\tcheck_cuda_errors(cudaMalloc(&ret, bytes));\n\t\t\treturn ret;\n\t\t}\n\n\t\tvoid deallocate(void* p, std::size_t size) {//NOLINT(readability-convert-member-functions-to-static) Method is designed to be a non-static class member\n\t\t\t(void) size;\n\t\t\tcheck_cuda_errors(cudaFree(p));\n\t\t}\n\t};\n\n\tstruct TempAllocator {\n\t\tint did;\n\n\t\texplicit TempAllocator(int did)\n\t\t\t: did {did} {}\n\n\t\tvoid* allocate(std::size_t bytes) {//NOLINT(readability-convert-member-functions-to-static) Method is designed to be a non-static class member\n\t\t\treturn Cuda::ref_cuda_context(did).borrow(bytes);\n\t\t}\n\n\t\tvoid deallocate(void* p, std::size_t size) {//NOLINT(readability-convert-member-functions-to-static) Method is designed to be a non-static class member\n\t\t\t(void) p;\n\t\t\t(void) size;\n\t\t}\n\t};\n\n\tstruct Intermediates {\n\t\tvoid* base;\n\n\t\tint* d_tmp;\n\t\tint* active_block_marks;\n\t\tint* destinations;\n\t\tint* sources;\n\t\tint* bin_sizes;\n\t\tfloat* d_max_vel;\n\t\t//NOLINTBEGIN(cppcoreguidelines-pro-bounds-pointer-arithmetic) Current c++ version does not yet support std::span\n\t\tvoid alloc(size_t max_block_count) {\n\t\t\t//NOLINTBEGIN(readability-magic-numbers) Magic numbers are variable count\n\t\t\tcheck_cuda_errors(cudaMalloc(&base, sizeof(int) * (max_block_count * 5 + 1)));\n\n\t\t\td_tmp\t\t\t = static_cast(base);\n\t\t\tactive_block_marks = static_cast(static_cast(static_cast(base) + sizeof(int) * max_block_count));\n\t\t\tdestinations\t = static_cast(static_cast(static_cast(base) + sizeof(int) * max_block_count * 2));\n\t\t\tsources\t\t\t = static_cast(static_cast(static_cast(base) + sizeof(int) * max_block_count * 3));\n\t\t\tbin_sizes\t\t = static_cast(static_cast(static_cast(base) + sizeof(int) * max_block_count * 4));\n\t\t\td_max_vel\t\t = static_cast(static_cast(static_cast(base) + sizeof(int) * max_block_count * 5));\n\t\t\t//NOLINTEND(readability-magic-numbers)\n\t\t}\n\t\t//NOLINTEND(cppcoreguidelines-pro-bounds-pointer-arithmetic)\n\t\tvoid dealloc() const {\n\t\t\tcudaDeviceSynchronize();\n\t\t\tcheck_cuda_errors(cudaFree(base));\n\t\t}\n\t\tvoid resize(size_t max_block_count) {\n\t\t\tdealloc();\n\t\t\talloc(max_block_count);\n\t\t}\n\t};\n\n\t///\n\t/// animation runtime settings\n\tfloat dt;\n\tfloat next_dt;\n\tfloat dt_default;\n\tfloat cur_time;\n\tfloat max_vel;\n\tuint64_t cur_frame;\n\tuint64_t cur_step;\n\tuint64_t fps;\n\t/// data on device, double buffering\n\tstd::vector> collision_objs;\n\tstd::array, BIN_COUNT> grid_blocks;\n\tstd::array, BIN_COUNT> particle_bins;\n\tstd::array>, BIN_COUNT> partitions;///< with halo info\n\tstd::vector input_halo_grid_blocks;\n\tstd::vector output_halo_grid_blocks;\n\t// std::vector inputHaloParticleBlocks,\n\t// outputHaloParticleBlocks;\n\tvec particles;\n\n\tstd::array tmps = {};\n\n\t// halo data\n\tvec halo_block_ids;\n\n\t/// data on host\n\tstatic_assert(std::is_same_v, \"block index type is not int\");\n\tchar rollid;\n\tstd::array cur_num_active_blocks\t\t\t\t = {};\n\tstd::array cur_num_active_bins\t\t\t\t\t = {};\n\tstd::array, config::G_DEVICE_COUNT> checked_counts = {};\n\tvec max_vels;\n\tvec partition_block_count;\n\tvec nbcount;\n\tvec exterior_block_count;\n\tvec bincount;\t\t\t ///< num blocks\n\tvec particle_counts;///< num particles\n\tstd::array, config::G_DEVICE_COUNT + 1> durations;\n\tstd::array>, config::G_DEVICE_COUNT> models;\n\tInstance host_data;\n\n\t/// control\n\tbool b_running;\n\tstd::array>, config::G_DEVICE_COUNT> jobs;\n\tstd::array ths;///< thread is not trivial\n\tstd::mutex mut_slave;\n\tstd::mutex mut_ctrl;\n\tstd::condition_variable cv_slave;\n\tstd::condition_variable cv_ctrl;\n\tstd::atomic_uint idle_count {0};\n\n\t/// computations per substep\n\tstd::vector> init_tasks;\n\tstd::vector> loop_tasks;\n\n\tMgspBenchmark()\n\t\t: dt()\n\t\t, next_dt()\n\t\t, dt_default(DEFAULT_DT)\n\t\t, cur_time(0.f)\n\t\t, max_vel()\n\t\t, rollid(0)\n\t\t, cur_frame(0)\n\t\t, cur_step(0)\n\t\t, fps(DEFAULT_FPS)\n\t\t, host_data()\n\t\t, b_running(true) {\n\t\t// data\n\t\thost_data = spawn(host_allocator {});\n\t\tcollision_objs.resize(config::G_DEVICE_COUNT);\n\t\tinit_particles<0>();\n\t\tfmt::print(\n\t\t\t\"{} -vs- {}\\n\",\n\t\t\tmatch(particle_bins[0][0])([&](auto& particle_buffer) {\n\t\t\t\treturn particle_buffer.size;\n\t\t\t}),\n\t\t\tmatch(particle_bins[0][1])([&](auto& particle_buffer) {\n\t\t\t\treturn particle_buffer.size;\n\t\t\t})\n\t\t);\n\t\t// tasks\n\t\tfor(int did = 0; did < config::G_DEVICE_COUNT; ++did) {\n\t\t\tths[did] = std::thread(\n\t\t\t\t[this](int did) {\n\t\t\t\t\tthis->gpu_worker(did);\n\t\t\t\t},\n\t\t\t\tdid\n\t\t\t);\n\t\t}\n\t}\n\n\t~MgspBenchmark() {\n\t\tauto is_empty = [this]() {\n\t\t\tfor(int did = 0; did < config::G_DEVICE_COUNT; ++did) {\n\t\t\t\tif(!jobs[did].empty()) {\n\t\t\t\t\treturn false;\n\t\t\t\t}\n\t\t\t}\n\t\t\treturn true;\n\t\t};\n\t\tdo {\n\t\t\tcv_slave.notify_all();\n\t\t} while(!is_empty());\n\t\tb_running = false;\n\t\tfor(auto& th: ths) {\n\t\t\tth.join();\n\t\t}\n\t}\n\n\t//TODO: Maybe implement?\n\tMgspBenchmark(MgspBenchmark& other)\t\t\t\t= delete;\n\tMgspBenchmark(MgspBenchmark&& other)\t\t\t= delete;\n\tMgspBenchmark& operator=(MgspBenchmark& other)\t= delete;\n\tMgspBenchmark& operator=(MgspBenchmark&& other) = delete;\n\n\ttemplate\n\tvoid init_particles() {\n\t\tauto& cu_dev = Cuda::ref_cuda_context(I);\n\t\tcu_dev.set_context();\n\t\ttmps[I].alloc(config::G_MAX_ACTIVE_BLOCK);\n\t\tfor(int copyid = 0; copyid < BIN_COUNT; copyid++) {\n\t\t\tgrid_blocks[copyid].emplace_back(DeviceAllocator {});\n\t\t\tparticle_bins[copyid].emplace_back(ParticleBuffer {DeviceAllocator {}});\n\t\t\tpartitions[copyid].emplace_back(DeviceAllocator {}, config::G_MAX_ACTIVE_BLOCK);\n\t\t}\n\t\tcu_dev.syncStream();\n\t\tinput_halo_grid_blocks.emplace_back(config::G_DEVICE_COUNT);\n\t\toutput_halo_grid_blocks.emplace_back(config::G_DEVICE_COUNT);\n\t\tparticles[I]\t\t\t = static_cast(spawn(DeviceAllocator {}));\n\t\tchecked_counts[I][0]\t = 0;\n\t\tchecked_counts[I][1]\t = 0;\n\t\tcur_num_active_blocks[I] = config::G_MAX_ACTIVE_BLOCK;\n\t\tcur_num_active_bins[I]\t = config::G_MAX_PARTICLE_BIN;\n\t\t/// tail-recursion optimization\n\t\tif constexpr(I + 1 < config::G_DEVICE_COUNT) {\n\t\t\tinit_particles();\n\t\t}\n\t}\n\n\tvoid init_model(int devid, const std::vector>& model) {\n\t\tauto& cu_dev = Cuda::ref_cuda_context(devid);\n\t\tcu_dev.set_context();\n\t\tparticle_counts[devid] = model.size();\n\t\tfmt::print(\"init model[{}] with {} particles\\n\", devid, particle_counts[devid]);\n\t\tcudaMemcpyAsync(static_cast(&particles[devid].val_1d(_0, 0)), model.data(), sizeof(std::array) * model.size(), cudaMemcpyDefault, cu_dev.stream_compute());\n\t\tcu_dev.syncStream();\n\n\t\tstd::string fn = std::string {\"model\"} + \"_dev[\" + std::to_string(devid) + \"]_frame[0].bgeo\";\n\t\tIO::insert_job([fn, model]() {\n\t\t\twrite_partio(fn, model);\n\t\t});\n\t\tIO::flush();\n\t}\n\n\t//TODO: Check magic numbers and replace by constants\n\t//NOLINTBEGIN(readability-magic-numbers)\n\tvoid init_boundary(const std::string& fn) {\n\t\tinit_from_signed_distance_file(fn, vec {static_cast(1024), static_cast(1024), static_cast(512)}, host_data);\n\t\tfor(int did = 0; did < config::G_DEVICE_COUNT; ++did) {\n\t\t\tauto& cu_dev = Cuda::ref_cuda_context(did);\n\t\t\tcu_dev.set_context();\n\t\t\tcollision_objs[did] = SignedDistanceGrid {DeviceAllocator {}};\n\t\t\tcollision_objs[did]->init(host_data, cu_dev.stream_compute());\n\t\t\tcu_dev.syncStream();\n\t\t}\n\t}\n\t//NOLINTEND(readability-magic-numbers)\n\n\ttemplate\n\tvoid exclusive_scan(int count, int const* const in, int* out, CudaContext& cu_dev) {\n//TODO:Not sure, what it does. Maybe remove or create names control macro for activation\n#if 1//NOLINT(readability-avoid-unconditional-preprocessor-if)\n\t\tauto policy = thrust::cuda::par.on(static_cast(cu_dev.stream_compute()));\n\t\tthrust::exclusive_scan(policy, get_device_ptr(in), get_device_ptr(in) + count, get_device_ptr(out));\n#else\n\t\tstd::size_t temp_storage_bytes = 0;\n\t\tauto plus_op\t\t\t\t = [] __device__(const int& a, const int& b) {\n\t\t\t return a + b;\n\t\t};\n\t\tcheck_cuda_errors(cub::DeviceScan::ExclusiveScan(nullptr, temp_storage_bytes, in, out, plus_op, 0, count, cu_dev.stream_compute()));\n\t\tvoid* d_tmp = tmps[cu_dev.get_dev_id()].d_tmp;\n\t\tcheck_cuda_errors(cub::DeviceScan::ExclusiveScan(d_tmp, temp_storage_bytes, in, out, plus_op, 0, count, cu_dev.stream_compute()));\n#endif\n\t}\n\n\tfloat get_mass(int did) {\n\t\treturn match(particle_bins[rollid][did])([&](const auto& particle_buffer) {\n\t\t\treturn particle_buffer.mass;\n\t\t});\n\t}\n\n\tvoid check_capacity(int did) {\n\t\t//TODO: Is that right? Maybe create extra parameter for this?\n\t\t//NOLINTBEGIN(readability-magic-numbers) Magic numbers are resize thresholds?\n\t\tif(exterior_block_count[did] > cur_num_active_blocks[did] * config::NUM_DIMENSIONS / 4 && checked_counts[did][0] == 0) {\n\t\t\tcur_num_active_blocks[did] = cur_num_active_blocks[did] * config::NUM_DIMENSIONS / 2;\n\t\t\tchecked_counts[did][0]\t = 2;\n\t\t\tfmt::print(fmt::emphasis::bold, \"resizing blocks {} -> {}\\n\", exterior_block_count[did], cur_num_active_blocks[did]);\n\t\t}\n\t\tif(bincount[did] > cur_num_active_bins[did] * config::NUM_DIMENSIONS / 4 && checked_counts[did][1] == 0) {\n\t\t\tcur_num_active_bins[did] = cur_num_active_bins[did] * config::NUM_DIMENSIONS / 2;\n\t\t\tchecked_counts[did][1]\t = 2;\n\t\t\tfmt::print(fmt::emphasis::bold, \"resizing bins {} -> {}\\n\", bincount[did], cur_num_active_bins[did]);\n\t\t}\n\t\t//NOLINTEND(readability-magic-numbers)\n\t}\n\n\t/// thread local ctrl flow\n\tvoid gpu_worker(int did) {\n\t\tauto wait = [did, this]() {\n\t\t\tstd::unique_lock lk {this->mut_slave};\n\t\t\tthis->cv_slave.wait(lk, [did, this]() {\n\t\t\t\treturn !this->b_running || !this->jobs[did].empty();\n\t\t\t});\n\t\t};\n\t\tauto signal = [this]() {\n\t\t\tstd::unique_lock lk {this->mut_ctrl};\n\t\t\tthis->idle_count.fetch_add(1);\n\t\t\tlk.unlock();\n\t\t\tthis->cv_ctrl.notify_one();\n\t\t};\n\t\tauto& cu_dev = Cuda::ref_cuda_context(did);\n\t\tcu_dev.set_context();\n\t\tfmt::print(fg(fmt::color::light_blue), \"{}-th gpu worker operates on GPU {}\\n\", did, cu_dev.get_dev_id());\n\t\twhile(this->b_running) {\n\t\t\twait();\n\t\t\tauto job = this->jobs[did].try_pop();\n\t\t\tif(job) {\n\t\t\t\t(*job)(did);\n\t\t\t}\n\t\t\tsignal();\n\t\t}\n\t\tfmt::print(fg(fmt::color::light_blue), \"{}-th gpu worker exits\\n\", did);\n\t}\n\n\tvoid sync() {\n\t\tstd::unique_lock lk {mut_ctrl};\n\t\tcv_ctrl.wait(lk, [this]() {\n\t\t\treturn this->idle_count == config::G_DEVICE_COUNT;\n\t\t});\n\t\tfmt::print(\n\t\t\tfmt::emphasis::bold,\n\t\t\t\"-----------------------------------------------------------\"\n\t\t\t\"-----\\n\"\n\t\t);\n\t}\n\n\tvoid issue(const std::function& job) {\n\t\tstd::unique_lock lk {mut_slave};\n\t\tfor(int did = 0; did < config::G_DEVICE_COUNT; ++did) {\n\t\t\tjobs[did].push(job);\n\t\t}\n\t\tidle_count = 0;\n\t\tlk.unlock();\n\t\tcv_slave.notify_all();\n\t}\n\n\t//FIXME: no signed integer bitwise operations! (rollid)\n\t//TODO: Check magic numbers and replace by constants\n\t//NOLINTBEGIN(cppcoreguidelines-pro-bounds-pointer-arithmetic, readability-magic-numbers) Current c++ version does not yet support std::span\n\tvoid main_loop() {\n\t\t/// initial\n\t\tconst float initial_next_time = 1.0f / static_cast(fps);\n\t\tdt\t\t\t\t\t\t\t = compute_dt(0.0f, cur_time, initial_next_time, dt_default);\n\t\tfmt::print(fmt::emphasis::bold, \"{} --{}--> {}, defaultDt: {}\\n\", cur_time, dt, initial_next_time, dt_default);\n\t\tinitial_setup();\n\t\tcur_time = dt;\n\t\tfor(cur_frame = 1; cur_frame <= config::G_TOTAL_FRAME_COUNT; ++cur_frame) {\n\t\t\tconst float next_time = static_cast(cur_frame) / static_cast(fps);\n\t\t\tfor(; cur_time < next_time; cur_time += dt, cur_step++) {\n\t\t\t\t/// max grid vel\n\t\t\t\tissue([this](int did) {\n\t\t\t\t\tauto& cu_dev = Cuda::ref_cuda_context(did);\n\t\t\t\t\t/// check capacity\n\t\t\t\t\tcheck_capacity(did);\n\t\t\t\t\tfloat* d_max_vel = tmps[did].d_max_vel;\n\t\t\t\t\tCudaTimer timer {cu_dev.stream_compute()};\n\t\t\t\t\ttimer.tick();\n\t\t\t\t\tcheck_cuda_errors(cudaMemsetAsync(d_max_vel, 0, sizeof(float), cu_dev.stream_compute()));\n\t\t\t\t\tif(collision_objs[did]) {\n\t\t\t\t\t\tcu_dev.compute_launch(\n\t\t\t\t\t\t\t{(nbcount[did] + config::G_NUM_GRID_BLOCKS_PER_CUDA_BLOCK - 1) / config::G_NUM_GRID_BLOCKS_PER_CUDA_BLOCK, config::G_NUM_WARPS_PER_CUDA_BLOCK * 32, config::G_NUM_WARPS_PER_CUDA_BLOCK},\n\t\t\t\t\t\t\tupdate_grid_velocity_query_max,\n\t\t\t\t\t\t\tstatic_cast(nbcount[did]),\n\t\t\t\t\t\t\t// grid_blocks[0][did], partitions[rollid][did], dt, d_max_vel);\n\t\t\t\t\t\t\tgrid_blocks[0][did],\n\t\t\t\t\t\t\tpartitions[rollid][did],\n\t\t\t\t\t\t\tdt,\n\t\t\t\t\t\t\tstatic_cast(*collision_objs[did]),\n\t\t\t\t\t\t\td_max_vel\n\t\t\t\t\t\t);\n\t\t\t\t\t} else {\n\t\t\t\t\t\tcu_dev.compute_launch(\n\t\t\t\t\t\t\t{(nbcount[did] + config::G_NUM_GRID_BLOCKS_PER_CUDA_BLOCK - 1) / config::G_NUM_GRID_BLOCKS_PER_CUDA_BLOCK, config::G_NUM_WARPS_PER_CUDA_BLOCK * 32, config::G_NUM_WARPS_PER_CUDA_BLOCK},\n\t\t\t\t\t\t\tupdate_grid_velocity_query_max,\n\t\t\t\t\t\t\tstatic_cast(nbcount[did]),\n\t\t\t\t\t\t\t// grid_blocks[0][did], partitions[rollid][did], dt, d_max_vel);\n\t\t\t\t\t\t\tgrid_blocks[0][did],\n\t\t\t\t\t\t\tpartitions[rollid][did],\n\t\t\t\t\t\t\tdt,\n\t\t\t\t\t\t\td_max_vel\n\t\t\t\t\t\t);\n\t\t\t\t\t}\n\t\t\t\t\tcheck_cuda_errors(cudaMemcpyAsync(&max_vels[did], d_max_vel, sizeof(float), cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\t\t\t\ttimer.tock(fmt::format(\"GPU[{}] frame {} step {} grid_update_query\", did, cur_frame, cur_step));\n\t\t\t\t});\n\t\t\t\tsync();\n\n\t\t\t\t/// host: compute maxvel & next dt\n\t\t\t\tfloat max_vel = 0.f;\n\t\t\t\tfor(int did = 0; did < config::G_DEVICE_COUNT; ++did) {\n\t\t\t\t\tif(max_vels[did] > max_vel) {\n\t\t\t\t\t\tmax_vel = max_vels[did];\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\tmax_vel = std::sqrt(max_vel);\n\t\t\t\tnext_dt = compute_dt(max_vel, cur_time, next_time, dt_default);\n\t\t\t\tfmt::print(fmt::emphasis::bold, \"{} --{}--> {}, defaultDt: {}, max_vel: {}\\n\", cur_time, next_dt, next_time, dt_default, max_vel);\n\n\t\t\t\t/// g2p2g\n\t\t\t\tissue([this](int did) {\n\t\t\t\t\tauto& cu_dev = Cuda::ref_cuda_context(did);\n\t\t\t\t\tCudaTimer timer {cu_dev.stream_compute()};\n\n\t\t\t\t\t/// check capacity\n\t\t\t\t\tif(checked_counts[did][1] > 0) {\n\t\t\t\t\t\tmatch(particle_bins[rollid ^ 1][did])([this, &did](auto& particle_buffer) {\n\t\t\t\t\t\t\tparticle_buffer.resize(DeviceAllocator {}, cur_num_active_bins[did]);\n\t\t\t\t\t\t});\n\t\t\t\t\t\tchecked_counts[did][1]--;\n\t\t\t\t\t}\n\n\t\t\t\t\ttimer.tick();\n\t\t\t\t\t// grid\n\t\t\t\t\tgrid_blocks[1][did].reset(nbcount[did], cu_dev);\n\t\t\t\t\t// adv map\n\t\t\t\t\tcheck_cuda_errors(cudaMemsetAsync(partitions[rollid][did].cell_particle_counts, 0, sizeof(int) * exterior_block_count[did] * config::G_BLOCKVOLUME, cu_dev.stream_compute()));\n\t\t\t\t\t// g2p2g\n\t\t\t\t\tmatch(particle_bins[rollid][did])([this, &did, &cu_dev](const auto& particle_buffer) {\n\t\t\t\t\t\tif(partitions[rollid][did].h_count) {\n\t\t\t\t\t\t\tcu_dev.compute_launch({partitions[rollid][did].h_count, 128, (512 * 3 * 4) + (512 * 4 * 4)}, g2p2g, dt, next_dt, static_cast(partitions[rollid][did].halo_blocks), particle_buffer, get>(particle_bins[rollid ^ 1][did]), partitions[rollid ^ 1][did], partitions[rollid][did], grid_blocks[0][did], grid_blocks[1][did]);\n\t\t\t\t\t\t}\n\t\t\t\t\t});\n\t\t\t\t\tcu_dev.syncStream();\n\t\t\t\t\ttimer.tock(fmt::format(\"GPU[{}] frame {} step {} halo_g2p2g\", did, cur_frame, cur_step));\n\t\t\t\t});\n\t\t\t\tsync();\n\n\t\t\t\tcollect_halo_grid_blocks();\n\n\t\t\t\tissue([this](int did) {\n\t\t\t\t\tauto& cu_dev = Cuda::ref_cuda_context(did);\n\t\t\t\t\tCudaTimer timer {cu_dev.stream_compute()};\n\n\t\t\t\t\ttimer.tick();\n\t\t\t\t\tmatch(particle_bins[rollid][did])([this, &did, &cu_dev](const auto& particle_buffer) {\n\t\t\t\t\t\tcu_dev.compute_launch({partition_block_count[did], 128, (512 * 3 * 4) + (512 * 4 * 4)}, g2p2g, dt, next_dt, static_cast(nullptr), particle_buffer, get>(particle_bins[rollid ^ 1][did]), partitions[rollid ^ 1][did], partitions[rollid][did], grid_blocks[0][did], grid_blocks[1][did]);\n\t\t\t\t\t});\n\t\t\t\t\ttimer.tock(fmt::format(\"GPU[{}] frame {} step {} non_halo_g2p2g\", did, cur_frame, cur_step));\n\t\t\t\t\tif(checked_counts[did][0] > 0) {\n\t\t\t\t\t\tpartitions[rollid ^ 1][did].resize_partition(DeviceAllocator {}, cur_num_active_blocks[did]);\n\t\t\t\t\t\tchecked_counts[did][0]--;\n\t\t\t\t\t}\n\t\t\t\t});\n\t\t\t\tsync();\n\n\t\t\t\treduce_halo_grid_blocks();\n\n\t\t\t\tissue([this](int did) {\n\t\t\t\t\tauto& cu_dev = Cuda::ref_cuda_context(did);\n\t\t\t\t\tCudaTimer timer {cu_dev.stream_compute()};\n\t\t\t\t\ttimer.tick();\n\t\t\t\t\t/// mark particle blocks\n\t\t\t\t\tpartitions[rollid][did].build_particle_buckets(cu_dev, exterior_block_count[did]);\n\n\t\t\t\t\tint* active_block_marks = tmps[did].active_block_marks;\n\t\t\t\t\tint* destinations\t\t= tmps[did].destinations;\n\t\t\t\t\tint* sources\t\t\t= tmps[did].sources;\n\t\t\t\t\tcheck_cuda_errors(cudaMemsetAsync(active_block_marks, 0, sizeof(int) * nbcount[did], cu_dev.stream_compute()));\n\t\t\t\t\t/// mark grid blocks\n\t\t\t\t\tcu_dev.compute_launch({(nbcount[did] * config::G_BLOCKVOLUME + 127) / 128, 128}, mark_active_grid_blocks, static_cast(nbcount[did]), grid_blocks[1][did], active_block_marks);\n\t\t\t\t\tcu_dev.compute_launch({(exterior_block_count[did] + 1 + 127) / 128, 128}, mark_active_particle_blocks, exterior_block_count[did] + 1, partitions[rollid][did].particle_bucket_sizes, sources);\n\t\t\t\t\texclusive_scan(exterior_block_count[did] + 1, sources, destinations, cu_dev);\n\t\t\t\t\t/// building new partition\n\t\t\t\t\t// block count\n\t\t\t\t\tcheck_cuda_errors(cudaMemcpyAsync(partitions[rollid ^ 1][did].count, destinations + exterior_block_count[did], sizeof(int), cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\t\t\t\tcheck_cuda_errors(cudaMemcpyAsync(&partition_block_count[did], destinations + exterior_block_count[did], sizeof(int), cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\t\t\t\tcu_dev.compute_launch({(exterior_block_count[did] + 255) / 256, 256}, exclusive_scan_inverse, exterior_block_count[did], static_cast(destinations), sources);\n\t\t\t\t\t// indextable, activeKeys, particle_bucket_size, buckets\n\t\t\t\t\tpartitions[rollid ^ 1][did].reset_table(cu_dev.stream_compute());\n\t\t\t\t\tcu_dev.syncStream();\n\t\t\t\t\tcu_dev.compute_launch({partition_block_count[did], 128}, update_partition, static_cast(partition_block_count[did]), static_cast(sources), partitions[rollid][did], partitions[rollid ^ 1][did]);\n\t\t\t\t\t// bin_offsets\n\t\t\t\t\t{\n\t\t\t\t\t\tint* bin_sizes = tmps[did].bin_sizes;\n\t\t\t\t\t\tcu_dev.compute_launch({(partition_block_count[did] + 1 + 127) / 128, 128}, compute_bin_capacity, partition_block_count[did] + 1, static_cast(partitions[rollid ^ 1][did].particle_bucket_sizes), bin_sizes);\n\t\t\t\t\t\texclusive_scan(partition_block_count[did] + 1, bin_sizes, partitions[rollid ^ 1][did].bin_offsets, cu_dev);\n\t\t\t\t\t\tcheck_cuda_errors(cudaMemcpyAsync(&bincount[did], partitions[rollid ^ 1][did].bin_offsets + partition_block_count[did], sizeof(int), cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\t\t\t\t\tcu_dev.syncStream();\n\t\t\t\t\t}\n\t\t\t\t\ttimer.tock(fmt::format(\"GPU[{}] frame {} step {} update_partition\", did, cur_frame, cur_step));\n\n\t\t\t\t\t/// neighboring blocks\n\t\t\t\t\ttimer.tick();\n\t\t\t\t\tcu_dev.compute_launch({(partition_block_count[did] + 127) / 128, 128}, register_neighbor_blocks, static_cast(partition_block_count[did]), partitions[rollid ^ 1][did]);\n\t\t\t\t\tauto prev_neighbor_block_count = nbcount[did];\n\t\t\t\t\tcheck_cuda_errors(cudaMemcpyAsync(&nbcount[did], partitions[rollid ^ 1][did].count, sizeof(int), cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\t\t\t\tcu_dev.syncStream();\n\t\t\t\t\ttimer.tock(fmt::format(\"GPU[{}] frame {} step {} build_partition_for_grid\", did, cur_frame, cur_step));\n\n\t\t\t\t\t/// check capacity\n\t\t\t\t\tif(checked_counts[did][0] > 0) {\n\t\t\t\t\t\tgrid_blocks[0][did].resize(DeviceAllocator {}, cur_num_active_blocks[did]);\n\t\t\t\t\t}\n\t\t\t\t\t/// rearrange grid blocks\n\t\t\t\t\ttimer.tick();\n\t\t\t\t\tgrid_blocks[0][did].reset(exterior_block_count[did], cu_dev);\n\t\t\t\t\tcu_dev.compute_launch({prev_neighbor_block_count, config::G_BLOCKVOLUME}, copy_selected_grid_blocks, static_cast(partitions[rollid][did].active_keys), partitions[rollid ^ 1][did], static_cast(active_block_marks), grid_blocks[1][did], grid_blocks[0][did]);\n\t\t\t\t\tcu_dev.syncStream();\n\t\t\t\t\ttimer.tock(fmt::format(\"GPU[{}] frame {} step {} copy_grid_blocks\", did, cur_frame, cur_step));\n\t\t\t\t\t/// check capacity\n\t\t\t\t\tif(checked_counts[did][0] > 0) {\n\t\t\t\t\t\tgrid_blocks[1][did].resize(DeviceAllocator {}, cur_num_active_blocks[did]);\n\t\t\t\t\t\ttmps[did].resize(cur_num_active_blocks[did]);\n\t\t\t\t\t}\n\t\t\t\t});\n\t\t\t\tsync();\n\n\t\t\t\t/// halo tag\n\t\t\t\thalo_tagging();\n\n\t\t\t\tissue([this](int did) {\n\t\t\t\t\tauto& cu_dev = Cuda::ref_cuda_context(did);\n\t\t\t\t\tCudaTimer timer {cu_dev.stream_compute()};\n\n\t\t\t\t\ttimer.tick();\n\t\t\t\t\t/// exterior blocks\n\t\t\t\t\tcu_dev.compute_launch({(partition_block_count[did] + 127) / 128, 128}, register_exterior_blocks, static_cast(partition_block_count[did]), partitions[rollid ^ 1][did]);\n\t\t\t\t\tcheck_cuda_errors(cudaMemcpyAsync(&exterior_block_count[did], partitions[rollid ^ 1][did].count, sizeof(int), cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\t\t\t\tcu_dev.syncStream();\n\t\t\t\t\tfmt::print(fmt::emphasis::bold | fg(fmt::color::yellow), \"block count on device {}: {}, {}, {} [{}]; {} [{}]\\n\", did, partition_block_count[did], nbcount[did], exterior_block_count[did], cur_num_active_blocks[did], bincount[did], cur_num_active_bins[did]);\n\t\t\t\t\ttimer.tock(fmt::format(\"GPU[{}] frame {} step {} build_partition_for_particles\", did, cur_frame, cur_step));\n\t\t\t\t});\n\t\t\t\tsync();\n\t\t\t\trollid ^= 1;\n\t\t\t\tdt = next_dt;\n\t\t\t}\n\t\t\tissue([this](int did) {\n\t\t\t\tIO::flush();\n\t\t\t\toutput_model(did);\n\t\t\t});\n\t\t\tsync();\n\t\t\tfmt::print(\n\t\t\t\tfmt::emphasis::bold | fg(fmt::color::red),\n\t\t\t\t\"-----------------------------------------------------------\"\n\t\t\t\t\"-----\\n\"\n\t\t\t);\n\t\t}\n\t}\n\t//NOLINTEND(cppcoreguidelines-pro-bounds-pointer-arithmetic, readability-magic-numbers)\n\n\t//FIXME: no signed integer bitwise operations! (rollid)\n\t//TODO: Check magic numbers and replace by constants\n\t//NOLINTBEGIN(readability-magic-numbers)\n\tvoid output_model(int did) {\n\t\tauto& cu_dev = Cuda::ref_cuda_context(did);\n\t\tcu_dev.set_context();\n\t\tCudaTimer timer {cu_dev.stream_compute()};\n\t\ttimer.tick();\n\t\tint particle_count\t = 0;\n\t\tint* d_particle_count = static_cast(cu_dev.borrow(sizeof(int)));\n\t\tcheck_cuda_errors(cudaMemsetAsync(d_particle_count, 0, sizeof(int), cu_dev.stream_compute()));\n\t\tmatch(particle_bins[rollid][did])([this, &cu_dev, &did, &d_particle_count](const auto& particle_buffer) {\n\t\t\tcu_dev.compute_launch({partition_block_count[did], 128}, retrieve_particle_buffer, partitions[rollid][did], partitions[rollid ^ 1][did], particle_buffer, particles[did], d_particle_count);\n\t\t});\n\t\tcheck_cuda_errors(cudaMemcpyAsync(&particle_count, d_particle_count, sizeof(int), cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\tcu_dev.syncStream();\n\t\tfmt::print(fg(fmt::color::red), \"total number of particles {}\\n\", particle_count);\n\t\tmodels[did].resize(particle_count);\n\t\tcheck_cuda_errors(cudaMemcpyAsync(models[did].data(), (void*) &particles[did].val_1d(_0, 0), sizeof(std::array) * (particle_count), cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\tcu_dev.syncStream();\n\t\tstd::string fn = std::string {\"model\"} + \"_dev[\" + std::to_string(did) + \"]_frame[\" + std::to_string(cur_frame) + \"].bgeo\";\n\t\tIO::insert_job([fn, model = models[did]]() {\n\t\t\twrite_partio(fn, model);\n\t\t});\n\t\ttimer.tock(fmt::format(\"GPU[{}] frame {} step {} retrieve_particles\", did, cur_frame, cur_step));\n\t}\n\t//NOLINTEND(readability-magic-numbers)\n\n\t//FIXME: no signed integer bitwise operations! (rollid)\n\t//TODO: Check magic numbers and replace by constants\n\t//NOLINTBEGIN(cppcoreguidelines-pro-bounds-pointer-arithmetic, readability-magic-numbers)Current c++ version does not yet support std::span\n\tvoid initial_setup() {\n\t\tissue([this](int did) {\n\t\t\tauto& cu_dev = Cuda::ref_cuda_context(did);\n\t\t\tcu_dev.set_context();\n\t\t\tCudaTimer timer {cu_dev.stream_compute()};\n\t\t\ttimer.tick();\n\t\t\tcu_dev.compute_launch({(particle_counts[did] + 255) / 256, 256}, activate_blocks, particle_counts[did], particles[did], partitions[rollid ^ 1][did]);\n\t\t\tcheck_cuda_errors(cudaMemcpyAsync(&partition_block_count[did], partitions[rollid ^ 1][did].count, sizeof(int), cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\t\ttimer.tock(fmt::format(\"GPU[{}] step {} init_table\", did, cur_step));\n\n\t\t\ttimer.tick();\n\t\t\tcu_dev.reset_mem();\n\t\t\t// particle block\n\t\t\tcu_dev.compute_launch({(particle_counts[did] + 255) / 256, 256}, build_particle_cell_buckets, particle_counts[did], particles[did], partitions[rollid ^ 1][did]);\n\t\t\t// bucket, bin_offsets\n\t\t\tcu_dev.syncStream();\n\t\t\tpartitions[rollid ^ 1][did].build_particle_buckets(cu_dev, partition_block_count[did]);\n\t\t\t{\n\t\t\t\tint* bin_sizes = tmps[did].bin_sizes;\n\t\t\t\tcu_dev.compute_launch({(partition_block_count[did] + 1 + 127) / 128, 128}, compute_bin_capacity, partition_block_count[did] + 1, static_cast(partitions[rollid ^ 1][did].particle_bucket_sizes), bin_sizes);\n\t\t\t\texclusive_scan(partition_block_count[did] + 1, bin_sizes, partitions[rollid ^ 1][did].bin_offsets, cu_dev);\n\t\t\t\tcheck_cuda_errors(cudaMemcpyAsync(&bincount[did], partitions[rollid ^ 1][did].bin_offsets + partition_block_count[did], sizeof(int), cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\t\t\tcu_dev.syncStream();\n\t\t\t}\n\t\t\tmatch(particle_bins[rollid][did])([this, &cu_dev, &did](const auto& particle_buffer) {\n\t\t\t\tcu_dev.compute_launch({partition_block_count[did], 128}, array_to_buffer, particles[did], particle_buffer, partitions[rollid ^ 1][did]);\n\t\t\t});\n\t\t\t// grid block\n\t\t\tcu_dev.compute_launch({(partition_block_count[did] + 127) / 128, 128}, register_neighbor_blocks, static_cast(partition_block_count[did]), partitions[rollid ^ 1][did]);\n\t\t\tcheck_cuda_errors(cudaMemcpyAsync(&nbcount[did], partitions[rollid ^ 1][did].count, sizeof(int), cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\t\tcu_dev.syncStream();\n\t\t\tcu_dev.compute_launch({(partition_block_count[did] + 127) / 128, 128}, register_exterior_blocks, static_cast(partition_block_count[did]), partitions[rollid ^ 1][did]);\n\t\t\tcheck_cuda_errors(cudaMemcpyAsync(&exterior_block_count[did], partitions[rollid ^ 1][did].count, sizeof(int), cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\t\tcu_dev.syncStream();\n\t\t\ttimer.tock(fmt::format(\"GPU[{}] step {} init_partition\", did, cur_step));\n\n\t\t\tfmt::print(fmt::emphasis::bold | fg(fmt::color::yellow), \"block count on device {}: {}, {}, {} [{}]; {} [{}]\\n\", did, partition_block_count[did], nbcount[did], exterior_block_count[did], cur_num_active_blocks[did], bincount[did], cur_num_active_bins[did]);\n\t\t});\n\t\tsync();\n\n\t\thalo_tagging();\n\n\t\tissue([this](int did) {\n\t\t\tauto& cu_dev = Cuda::ref_cuda_context(did);\n\t\t\tCudaTimer timer {cu_dev.stream_compute()};\n\n\t\t\t/// need to copy halo tag info as well\n\t\t\tpartitions[rollid ^ 1][did].copy_to(partitions[rollid][did], exterior_block_count[did], cu_dev.stream_compute());\n\t\t\tcheck_cuda_errors(cudaMemcpyAsync(partitions[rollid][did].active_keys, partitions[rollid ^ 1][did].active_keys, sizeof(ivec3) * exterior_block_count[did], cudaMemcpyDefault, cu_dev.stream_compute()));\n\t\t\tcu_dev.syncStream();\n\n\t\t\ttimer.tick();\n\t\t\tgrid_blocks[0][did].reset(nbcount[did], cu_dev);\n\t\t\tcu_dev.compute_launch({(particle_counts[did] + 255) / 256, 256}, rasterize, particle_counts[did], particles[did], grid_blocks[0][did], partitions[rollid][did], dt, get_mass(did));\n\t\t\tcu_dev.compute_launch({partition_block_count[did], 128}, init_adv_bucket, static_cast(partitions[rollid][did].particle_bucket_sizes), partitions[rollid][did].blockbuckets);\n\t\t\tcu_dev.syncStream();\n\t\t\ttimer.tock(fmt::format(\"GPU[{}] step {} init_grid\", did, cur_step));\n\t\t});\n\t\tsync();\n\n\t\tcollect_halo_grid_blocks(0);\n\t\treduce_halo_grid_blocks(0);\n\t}\n\t//NOLINTEND(cppcoreguidelines-pro-bounds-pointer-arithmetic, readability-magic-numbers)\n\n\t//FIXME: no signed integer bitwise operations! (rollid)\n\t//TODO: Check magic numbers and replace by constants\n\t//NOLINTBEGIN(cppcoreguidelines-pro-bounds-pointer-arithmetic, readability-magic-numbers)Current c++ version does not yet support std::span\n\tvoid halo_tagging() {\n\t\tissue([this](int did) {\n\t\t\tauto& cu_dev = Cuda::ref_cuda_context(did);\n\t\t\tcu_dev.reset_mem();\n\t\t\tfor(int otherdid = 0; otherdid < config::G_DEVICE_COUNT; otherdid++) {\n\t\t\t\tif(otherdid != did) {\n\t\t\t\t\thalo_block_ids[did][otherdid] = static_cast(cu_dev.borrow(sizeof(ivec3) * nbcount[otherdid]));\n\t\t\t\t}\n\t\t\t}\n\t\t\t/// init halo blockids\n\t\t\toutput_halo_grid_blocks[did].init_blocks(TempAllocator {did}, nbcount[did]);\n\t\t\tinput_halo_grid_blocks[did].init_blocks(TempAllocator {did}, nbcount[did]);\n\t\t});\n\t\tsync();\n\t\tissue([this](int did) {\n\t\t\tauto& cu_dev = Cuda::ref_cuda_context(did);\n\t\t\t/// prepare counts\n\t\t\toutput_halo_grid_blocks[did].reset_counts(cu_dev.stream_compute());\n\t\t\tcu_dev.syncStream();\n\t\t\t/// sharing local active blocks\n\t\t\tfor(int otherdid = 0; otherdid < config::G_DEVICE_COUNT; otherdid++) {\n\t\t\t\tif(otherdid != did) {\n\t\t\t\t\tcheck_cuda_errors(cudaMemcpyAsync(halo_block_ids[otherdid][did], partitions[rollid ^ 1][did].active_keys, sizeof(ivec3) * nbcount[did], cudaMemcpyDefault, cu_dev.stream_spare(otherdid)));\n\t\t\t\t\tcu_dev.spare_event_record(otherdid);\n\t\t\t\t}\n\t\t\t}\n\t\t});\n\t\tsync();\n\t\tissue([this](int did) {\n\t\t\tauto& cu_dev = Cuda::ref_cuda_context(did);\n\t\t\tCudaTimer timer {cu_dev.stream_compute()};\n\t\t\ttimer.tick();\n\t\t\t/// init overlap marks\n\t\t\tpartitions[rollid ^ 1][did].reset_overlap_marks(nbcount[did], cu_dev.stream_compute());\n\t\t\tcu_dev.syncStream();\n\t\t\t/// receiving active blocks from other devices\n\t\t\tfor(int otherdid = 0; otherdid < config::G_DEVICE_COUNT; otherdid++) {\n\t\t\t\tif(otherdid != did) {\n\t\t\t\t\tcu_dev.spareStreamWaitForEvent(otherdid, Cuda::ref_cuda_context(otherdid).event_spare(did));\n\t\t\t\t\tcu_dev.spare_launch(otherdid, {(nbcount[otherdid] + 127) / 128, 128}, mark_overlapping_blocks, static_cast(nbcount[otherdid]), otherdid, static_cast(halo_block_ids[did][otherdid]), partitions[rollid ^ 1][did], output_halo_grid_blocks[did].counts + otherdid, output_halo_grid_blocks[did].buffers[otherdid]);\n\t\t\t\t\tcu_dev.spare_event_record(otherdid);\n\t\t\t\t\tcu_dev.computeStreamWaitForEvent(cu_dev.event_spare(otherdid));\n\t\t\t\t}\n\t\t\t}\n\t\t\t// self halo particle block\n\t\t\tpartitions[rollid ^ 1][did].reset_halo_count(cu_dev.stream_compute());\n\t\t\tcu_dev.compute_launch({(partition_block_count[did] + 127) / 128, 128}, collect_blockids_for_halo_reduction, static_cast(partition_block_count[did]), did, partitions[rollid ^ 1][did]);\n\t\t\t/// retrieve counts\n\t\t\tpartitions[rollid ^ 1][did].retrieve_halo_count(cu_dev.stream_compute());\n\t\t\toutput_halo_grid_blocks[did].retrieve_counts(cu_dev.stream_compute());\n\t\t\tcu_dev.syncStream();\n\t\t\ttimer.tock(fmt::format(\"GPU[{}] step {} halo_tagging\", did, cur_step));\n\n\t\t\tfmt::print(fg(fmt::color::green), \"halo particle blocks[{}]: {}\\n\", did, partitions[rollid ^ 1][did].h_count);\n\t\t\tfor(int otherdid = 0; otherdid < config::G_DEVICE_COUNT; otherdid++) {\n\t\t\t\tfmt::print(fg(fmt::color::green), \"halo grid blocks[{}][{}]: {}\\n\", did, otherdid, output_halo_grid_blocks[did].h_counts[otherdid]);\n\t\t\t}\n\t\t});\n\t\tsync();\n\t}\n\t//NOLINTEND(cppcoreguidelines-pro-bounds-pointer-arithmetic, readability-magic-numbers)\n\n\tvoid collect_halo_grid_blocks(int gid = 1) {\n\t\t/// init halo grid blocks\n\t\tissue([this](int did) {\n\t\t\tstd::vector counts(config::G_DEVICE_COUNT);\n\t\t\toutput_halo_grid_blocks[did].init_buffer(TempAllocator {did}, output_halo_grid_blocks[did].h_counts);\n\t\t\tfor(int otherdid = 0; otherdid < config::G_DEVICE_COUNT; otherdid++) {\n\t\t\t\tcounts[otherdid] = (otherdid != did) ? output_halo_grid_blocks[otherdid].h_counts[did] : 0;\n\t\t\t}\n\t\t\tinput_halo_grid_blocks[did].init_buffer(TempAllocator {did}, counts);\n\t\t});\n\t\tsync();\n\t\tissue([this, gid](int did) {\n\t\t\tauto& cu_dev = Cuda::ref_cuda_context(did);\n\t\t\tCppTimer timer {};\n\t\t\ttimer.tick();\n\t\t\t/// sharing local active blocks\n\t\t\tfor(int otherdid = 0; otherdid < config::G_DEVICE_COUNT; otherdid++) {\n\t\t\t\tif(otherdid != did) {\n\t\t\t\t\tif(output_halo_grid_blocks[did].h_counts[otherdid] > 0) {\n\t\t\t\t\t\tauto& count = output_halo_grid_blocks[did].h_counts[otherdid];\n\t\t\t\t\t\tcu_dev.spare_launch(otherdid, {count, config::G_BLOCKVOLUME}, collect_grid_blocks, grid_blocks[gid][did], partitions[rollid][did], output_halo_grid_blocks[did].buffers[otherdid]);\n\t\t\t\t\t\toutput_halo_grid_blocks[did].send(input_halo_grid_blocks[otherdid], did, otherdid, cu_dev.stream_spare(otherdid));\n\t\t\t\t\t\tcu_dev.spare_event_record(otherdid);\n\t\t\t\t\t} else {\n\t\t\t\t\t\tinput_halo_grid_blocks[otherdid].h_counts[did] = 0;\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t\ttimer.tock(fmt::format(\"GPU[{}] step {} collect_send_halo_grid\", did, cur_step));\n\t\t});\n\t\tsync();\n\t}\n\n\tvoid reduce_halo_grid_blocks(int gid = 1) {\n\t\tissue([this, gid](int did) {\n\t\t\tauto& cu_dev = Cuda::ref_cuda_context(did);\n\t\t\tCppTimer timer {};\n\t\t\ttimer.tick();\n\t\t\t/// receiving active blocks from other devices\n\t\t\tfor(int otherdid = 0; otherdid < config::G_DEVICE_COUNT; otherdid++) {\n\t\t\t\tif(otherdid != did) {\n\t\t\t\t\tif(input_halo_grid_blocks[did].h_counts[otherdid] > 0) {\n\t\t\t\t\t\tcu_dev.spareStreamWaitForEvent(otherdid, Cuda::ref_cuda_context(otherdid).event_spare(did));\n\t\t\t\t\t\tcu_dev.spare_launch(otherdid, {input_halo_grid_blocks[did].h_counts[otherdid], config::G_BLOCKVOLUME}, reduce_grid_blocks, grid_blocks[gid][did], partitions[rollid][did], input_halo_grid_blocks[did].buffers[otherdid]);\n\t\t\t\t\t\tcu_dev.spare_event_record(otherdid);\n\t\t\t\t\t\tcu_dev.computeStreamWaitForEvent(cu_dev.event_spare(otherdid));\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t\tcu_dev.syncStream();\n\t\t\ttimer.tock(fmt::format(\"GPU[{}] step {} receive_reduce_halo_grid\", did, cur_step));\n\t\t});\n\t\tsync();\n\t}\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Projects/MGSP/particle_buffer.cuh", "content": "#ifndef PARTICLE_BUFFER_CUH\n#define PARTICLE_BUFFER_CUH\n#include \n\n#include \"settings.h\"\n\n//NOLINTNEXTLINE(cppcoreguidelines-macro-usage) Macro usage necessary here for preprocessor if\n#define PRINT_NEGATIVE_BLOGNOS 1\n\nnamespace mn {\n\nusing ParticleBinDomain\t = AlignedDomain;\nusing ParticleBufferDomain = CompactDomain;\nusing ParticleArrayDomain = CompactDomain;\n//NOLINTBEGIN(cppcoreguidelines-avoid-non-const-global-variables, readability-identifier-naming) Check is buggy and reporst variable errors fro template arguments\nusing particle_bin4_ = Structural, ParticleBinDomain, attrib_layout::SOA, f32_, f32_, f32_, f32_>;\t\t\t\t\t\t\t\t\t\t\t\t\t\t///< J, pos\nusing particle_bin12_ = Structural, ParticleBinDomain, attrib_layout::SOA, f32_, f32_, f32_, f32_, f32_, f32_, f32_, f32_, f32_, f32_, f32_, f32_>;\t\t///< pos, F\nusing particle_bin13_ = Structural, ParticleBinDomain, attrib_layout::SOA, f32_, f32_, f32_, f32_, f32_, f32_, f32_, f32_, f32_, f32_, f32_, f32_, f32_>;///< pos, F, logJp\n//NOLINTEND(cppcoreguidelines-avoid-non-const-global-variables, readability-identifier-naming)\n\ntemplate\nstruct particle_bin_;\ntemplate<>\nstruct particle_bin_ : particle_bin4_ {};\ntemplate<>\nstruct particle_bin_ : particle_bin12_ {};\ntemplate<>\nstruct particle_bin_ : particle_bin13_ {};\ntemplate<>\nstruct particle_bin_ : particle_bin13_ {};\n\n//NOLINTBEGIN(cppcoreguidelines-avoid-non-const-global-variables, readability-identifier-naming) Check is buggy and reporst variable errors fro template arguments\ntemplate\nusing particle_buffer_ = Structural, ParticleBufferDomain, attrib_layout::AOS, ParticleBin>;\nusing particle_array_ = Structural, ParticleArrayDomain, attrib_layout::AOS, f32_, f32_, f32_>;\n//NOLINTEND(cppcoreguidelines-avoid-non-const-global-variables, readability-identifier-naming)\n\ntemplate\nstruct ParticleBufferImpl : Instance>> {\n\tstatic constexpr MaterialE MATERIAL_TYPE = Mt;\n\tusing base_t\t\t\t\t\t\t\t = Instance>>;\n\n\tstd::size_t num_active_blocks;\n\tint* cell_particle_counts;\n\tint* particle_bucket_sizes;\n\tint* cellbuckets;\n\tint* blockbuckets;\n\tint* bin_offsets;\n\n\ttemplate\n\texplicit ParticleBufferImpl(Allocator allocator)\n\t\t: base_t {spawn>, orphan_signature>(allocator)}\n\t\t, num_active_blocks()\n\t\t, cell_particle_counts(nullptr)\n\t\t, particle_bucket_sizes(nullptr)\n\t\t, cellbuckets(nullptr)\n\t\t, blockbuckets(nullptr)\n\t\t, bin_offsets(nullptr) {}\n\n\ttemplate\n\tvoid check_capacity(Allocator allocator, std::size_t capacity) {\n\t\tif(capacity > this->capacity)\n\t\t\tthis->resize(allocator, capacity);\n\t}\n};\n\n//NOTE: In subsequent classes some parameters are actually const and static, but they are nit declared as such to allow consistent access to the members\n//TODO: Maybe write accessors; Maybe create common baseclass(es) for accessing the parameters\n\ntemplate\nstruct ParticleBuffer;\ntemplate<>\nstruct ParticleBuffer : ParticleBufferImpl {\n\tusing base_t = ParticleBufferImpl;\n\n\t//NOLINTBEGIN(readability-magic-numbers) Parameter definitions\n\tfloat rho\t\t= config::DENSITY;\n\tfloat volume\t= (1.0f / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / config::MODEL_PPC);\n\tfloat mass\t\t= (config::DENSITY / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / config::MODEL_PPC);\n\tfloat bulk\t\t= 4e4;\n\tfloat gamma\t\t= 7.15f;\n\tfloat viscosity = 0.01f;\n\n\tvoid update_parameters(float density, float vol, float b, float g, float v) {\n\t\trho\t\t = density;\n\t\tvolume\t = vol;\n\t\tmass\t = volume * density;\n\t\tbulk\t = b;\n\t\tgamma\t = g;\n\t\tviscosity = v;\n\t}\n\t//NOLINTEND(readability-magic-numbers)\n\n\ttemplate\n\texplicit ParticleBuffer(Allocator allocator)\n\t\t: base_t {allocator} {}\n};\n\ntemplate<>\nstruct ParticleBuffer : ParticleBufferImpl {\n\tusing base_t = ParticleBufferImpl;\n\n\t//NOLINTBEGIN(readability-magic-numbers) Parameter definitions\n\tfloat rho\t = config::DENSITY;\n\tfloat volume = (10.f / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / config::MODEL_PPC);\n\tfloat mass\t = (config::DENSITY / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / config::MODEL_PPC);\n\tfloat e\t\t = config::YOUNGS_MODULUS;\n\tfloat nu\t = config::POISSON_RATIO;\n\tfloat lambda = config::YOUNGS_MODULUS * config::POISSON_RATIO / ((1 + config::POISSON_RATIO) * (1 - 2 * config::POISSON_RATIO));\n\tfloat mu\t = config::YOUNGS_MODULUS / (2 * (1 + config::POISSON_RATIO));\n\n\tvoid update_parameters(float density, float vol, float e, float nu) {\n\t\trho\t = density;\n\t\tvolume = vol;\n\t\tmass = volume * density;\n\t\tlambda = e * nu / ((1 + nu) * (1 - 2 * nu));\n\t\tmu\t = e / (2 * (1 + nu));\n\t}\n\t//NOLINTEND(readability-magic-numbers)\n\n\ttemplate\n\texplicit ParticleBuffer(Allocator allocator)\n\t\t: base_t {allocator} {}\n};\n\ntemplate<>\nstruct ParticleBuffer : ParticleBufferImpl {\n\tusing base_t = ParticleBufferImpl;\n\n\t//NOLINTBEGIN(readability-magic-numbers) Parameter definitions; consistent naming\n\tfloat rho\t = config::DENSITY;\n\tfloat volume = (10.f / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / config::MODEL_PPC);\n\tfloat mass\t = (config::DENSITY / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / config::MODEL_PPC);\n\tfloat r\t\t = config::YOUNGS_MODULUS;\n\tfloat nu\t = config::POISSON_RATIO;\n\tfloat lambda = config::YOUNGS_MODULUS * config::POISSON_RATIO / ((1 + config::POISSON_RATIO) * (1 - 2 * config::POISSON_RATIO));\n\tfloat mu\t = config::YOUNGS_MODULUS / (2 * (1 + config::POISSON_RATIO));\n\n\tstatic constexpr float LOG_JP_0 = 0.0f;\n\tfloat friction_angle\t\t\t= 30.f;\n\tfloat cohesion\t\t\t\t\t= 0.0f;\n\tfloat beta\t\t\t\t\t\t= 1.0f;\n\t// std::sqrt(2.f/3.f) * 2.f * std::sin(30.f/180.f*3.141592741f)\n\t// \t\t\t\t\t\t/ (3.f -\n\t// std::sin(30.f/180.f*3.141592741f))\n\tfloat yield_surface\t = 0.816496580927726f * 2.f * 0.5f / (3.f - 0.5f);\n\tbool volume_correction = true;\n\t//NOLINTEND(readability-magic-numbers)\n\n\ttemplate\n\texplicit ParticleBuffer(Allocator allocator)\n\t\t: base_t {allocator} {}\n};\n\ntemplate<>\nstruct ParticleBuffer : ParticleBufferImpl {\n\tusing base_t = ParticleBufferImpl;\n\n\t//NOLINTBEGIN(readability-magic-numbers) Parameter definitions\n\tfloat rho\t = config::DENSITY;\n\tfloat volume = (1.0f / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / config::MODEL_PPC);\n\tfloat mass\t = (config::DENSITY / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / (1u << config::DOMAIN_BITS) / config::MODEL_PPC);\n\tfloat e\t\t = config::YOUNGS_MODULUS;\n\tfloat nu\t = config::POISSON_RATIO;\n\tfloat lambda = config::YOUNGS_MODULUS * config::POISSON_RATIO / ((1 + config::POISSON_RATIO) * (1 - 2 * config::POISSON_RATIO));\n\tfloat mu\t = config::YOUNGS_MODULUS / (2 * (1 + config::POISSON_RATIO));\n\n\tfloat friction_angle\t\t\t= 45.f;\n\tfloat bm\t\t\t\t\t\t= 2.f / 3.f * (config::YOUNGS_MODULUS / (2 * (1 + config::POISSON_RATIO))) + (config::YOUNGS_MODULUS * config::POISSON_RATIO / ((1 + config::POISSON_RATIO) * (1 - 2 * config::POISSON_RATIO)));///< bulk modulus, kappa\n\tfloat xi\t\t\t\t\t\t= 0.8f;\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t///< hardening factor\n\tstatic constexpr float LOG_JP_0 = -0.01f;\n\tfloat beta\t\t\t\t\t\t= 0.5f;\n\tfloat mohr_columb_friction\t\t= 0.503599787772409;//< sqrt((T)2 / (T)3) * (T)2 * sin_phi / ((T)3 - sin_phi);\n\tfloat m\t\t\t\t\t\t\t= 1.850343771924453;//< mohr_columb_friction * (T)dim / sqrt((T)2 / ((T)6 - dim));\n\tfloat msqr\t\t\t\t\t\t= 3.423772074299613;\n\tbool hardening_on\t\t\t\t= true;\n\n\tvoid update_parameters(float density, float vol, float e, float nu, float be, float x) {\n\t\trho\t = density;\n\t\tvolume = vol;\n\t\tmass = volume * density;\n\t\tlambda = e * nu / ((1 + nu) * (1 - 2 * nu));\n\t\tmu\t = e / (2 * (1 + nu));\n\t\tbm\t = 2.f / 3.f * (e / (2 * (1 + nu))) + (e * nu / ((1 + nu) * (1 - 2 * nu)));\n\t\tbeta = be;\n\t\txi\t = x;\n\t}\n\t//NOLINTEND(readability-magic-numbers)\n\n\ttemplate\n\texplicit ParticleBuffer(Allocator allocator)\n\t\t: base_t {allocator} {}\n};\n\n/// conversion\n/// http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2018/p0608r3.html\nusing particle_buffer_t = variant, ParticleBuffer, ParticleBuffer, ParticleBuffer>;\n\nstruct ParticleArray : Instance {\n\tusing base_t = Instance;\n\n\tParticleArray() = default;\n\texplicit ParticleArray(base_t&& instance)//NOLINT(cppcoreguidelines-rvalue-reference-param-not-moved) Clang say, that std::move has no effect here\n\t\t: base_t(instance) {}\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Projects/MGSP/partition_domain.h", "content": "#ifndef PARTITION_DOMAIN_H\n#define PARTITION_DOMAIN_H\n#include \n#include \n\nnamespace mn {\n\ntemplate\nstruct PartitionDomain {\n\tusing index = std::array;\n\n\ttemplate\n\tconstexpr bool inside(Index&& id) const noexcept {\n\t\treturn self().inside(std::forward(id));\n\t}\n\ttemplate\n\tconstexpr bool within(Index&& id, Offset&& l, Offset&& u) const noexcept {\n\t\treturn self().within(std::forward(id), std::forward(l), std::forward(u));\n\t}\n\n protected:\n\tauto& self() noexcept {\n\t\treturn static_cast(*this);\n\t}\n};\n\ntemplate\nstruct BoxDomain : PartitionDomain, Tn, Dim> {\n\tusing base_t = PartitionDomain, Tn, Dim>;\n\tusing index\t = typename base_t::index;\n\n\tindex min;\n\tindex max;\n\n\tconstexpr BoxDomain() noexcept = default;\n\n\tconstexpr BoxDomain(index lower, index upper) {\n\t\tfor(int d = 0; d < Dim; ++d) {\n\t\t\tmin[d] = lower[d];\n\t\t\tmax[d] = upper[d];\n\t\t}\n\t}\n\n\tconstexpr BoxDomain(vec lower, vec upper) {\n\t\tfor(int d = 0; d < Dim; ++d) {\n\t\t\tmin[d] = lower[d];\n\t\t\tmax[d] = upper[d];\n\t\t}\n\t}\n\n\ttemplate\n\tconstexpr bool inside(Index&& id) const noexcept {\n\t\tfor(int d = 0; d < Dim; ++d) {\n\t\t\tif(id[d] < min[d] || id[d] > max[d]) {\n\t\t\t\treturn false;\n\t\t\t}\n\t\t}\n\t\treturn true;\n\t}\n\n\ttemplate\n\tconstexpr bool within(Index&& id, Offset&& l, Offset&& u) const noexcept {\n\t\tfor(int d = 0; d < Dim; ++d) {\n\t\t\tif(id[d] < min[d] + l[d] || id[d] > max[d] + u[d]) {\n\t\t\t\treturn false;\n\t\t\t}\n\t\t}\n\t\treturn true;\n\t}\n};\n\n}// namespace mn\n\n#endif" }, { "path": "Projects/MGSP/settings.h", "content": "#ifndef SETTINGS_H\n#define SETTINGS_H\n#include \n#include \n\n#include \n\n#include \"partition_domain.h\"\n\nnamespace mn {\n\nusing ivec3\t = vec;\nusing vec3\t = vec;\nusing vec9\t = vec;\nusing vec3x3 = vec;\nusing vec3x4 = vec;\nusing vec3x3x3 = vec;\n\n/// sand = Drucker Prager Plasticity, StvkHencky Elasticity\nenum class MaterialE {\n\tJ_FLUID = 0,\n\tFIXED_COROTATED,\n\tSAND,\n\tNACC,\n\tTOTAL\n};\n\n/// https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html, F.3.16.5\n/// benchmark setup\nnamespace config {\n\tconstexpr int G_DEVICE_COUNT = 2;\n\tconstexpr MaterialE get_material_type(int did) noexcept {\n\t\t(void) did;\n\n\t\treturn MaterialE::J_FLUID;\n\t}\n\tconstexpr int G_TOTAL_FRAME_COUNT = 60;\n\tconstexpr int NUM_DIMENSIONS\t = 3;\n\n\tconstexpr int GBPCB\t\t\t\t\t\t\t = 16;\n\tconstexpr int G_NUM_GRID_BLOCKS_PER_CUDA_BLOCK = GBPCB;\n\tconstexpr int G_NUM_WARPS_PER_GRID_BLOCK\t = 1;\n\tconstexpr int G_NUM_WARPS_PER_CUDA_BLOCK\t = GBPCB;\n\tconstexpr int G_PARTICLE_BATCH_CAPACITY\t\t = 128;\n\n\tconstexpr float MODEL_PPC\t= 8.0f;\n\tconstexpr float G_MODEL_PPC = MODEL_PPC;\n\tconstexpr float CFL\t\t\t= 0.5f;\n\n\t// background_grid\n\tconstexpr int BLOCK_BITS\t\t\t = 2;\n\tconstexpr int DOMAIN_BITS\t\t\t = 8;\n\tconstexpr float DXINV\t\t\t\t = (1.0f * (1u << DOMAIN_BITS));\n\tconstexpr int G_DOMAIN_BITS\t\t\t = DOMAIN_BITS;\n\tconstexpr int G_DOMAIN_SIZE\t\t\t = (1 << DOMAIN_BITS);\n\tconstexpr float G_BOUNDARY_CONDITION = 2.0;\n\tconstexpr float G_DX\t\t\t\t = 1.f / DXINV;\n\tconstexpr float G_DX_INV\t\t\t = DXINV;\n\tconstexpr float G_D_INV\t\t\t\t = 4.f * DXINV * DXINV;\n\tconstexpr int G_BLOCKBITS\t\t\t = BLOCK_BITS;\n\tconstexpr int G_BLOCKSIZE\t\t\t = (1 << BLOCK_BITS);\n\tconstexpr int G_BLOCKMASK\t\t\t = ((1 << BLOCK_BITS) - 1);\n\tconstexpr int G_BLOCKVOLUME\t\t\t = (1 << (BLOCK_BITS * 3));\n\tconstexpr int G_GRID_BITS\t\t\t = (DOMAIN_BITS - BLOCK_BITS);\n\tconstexpr int G_GRID_SIZE\t\t\t = (1 << (DOMAIN_BITS - BLOCK_BITS));\n\n\t// partition domains\n\t//NOLINTBEGIN(readability-magic-numbers) Numbers are used for dividing domains\n\tconstexpr BoxDomain get_domain(int did) noexcept {\n\t\tconstexpr int LEN = G_GRID_SIZE / 2;\n\t\tBoxDomain domain {};\n\t\tfor(int d = 0; d < NUM_DIMENSIONS; ++d) {\n\t\t\tdomain.min[d] = 0;\n\t\t\tdomain.max[d] = G_GRID_SIZE - 1;\n\t\t}\n\t\tif constexpr(G_DEVICE_COUNT == 1) {\n\t\t\t/// default\n\t\t} else if(G_DEVICE_COUNT == 2) {\n\t\t\tif(did == 0) {\n\t\t\t\tdomain.max[0] = LEN;\n\t\t\t} else if(did == 1) {//NOLINT(hicpp-multiway-paths-covered) Otherwise unchanged\n\t\t\t\tdomain.min[0] = LEN + 1;\n\t\t\t}\n\t\t} else if(G_DEVICE_COUNT <= 4 && G_DEVICE_COUNT >= 3) {\n\t\t\tdomain.min[0] = ((did & 2) != 0) ? LEN + 1 : 0;\n\t\t\tdomain.min[2] = ((did & 1) != 0) ? LEN + 1 : 0;\n\t\t\tdomain.max[0] = ((did & 2) != 0) ? G_GRID_SIZE - 1 : LEN;\n\t\t\tdomain.max[2] = ((did & 1) != 0) ? G_GRID_SIZE - 1 : LEN;\n\t\t} else {\n\t\t\tdomain.max[0] = domain.max[1] = domain.max[2] = -3;\n\t\t}\n\t\treturn domain;\n\t}\n\t//NOLINTEND(readability-magic-numbers)\n\n\t// particle\n\tconstexpr int MAX_PARTICLES_IN_CELL\t = 128;\n\tconstexpr int G_MAX_PARTICLES_IN_CELL = MAX_PARTICLES_IN_CELL;\n\tconstexpr int G_BIN_CAPACITY\t\t = 32;\n\tconstexpr int G_PARTICLE_NUM_PER_BLOCK = (MAX_PARTICLES_IN_CELL * (1 << (BLOCK_BITS * 3)));\n\n\t// material parameters\n\tconstexpr float DENSITY\t\t = 1e3;\n\tconstexpr float YOUNGS_MODULUS = 5e3;\n\tconstexpr float POISSON_RATIO = 0.4f;\n\n\t//\n\tconstexpr float G_GRAVITY = -9.8f * 0.5f;\n\n\t/// only used on host\n\tconstexpr int G_MAX_PARTICLE_NUM = 2000000;\n\tconstexpr int G_MAX_ACTIVE_BLOCK = 12000;/// 62500 bytes for active mask\n\tconstexpr std::size_t calc_particle_bin_count(std::size_t num_active_blocks) noexcept {\n\t\treturn num_active_blocks * (G_MAX_PARTICLES_IN_CELL * G_BLOCKVOLUME / G_BIN_CAPACITY);\n\t}\n\tconstexpr std::size_t G_MAX_PARTICLE_BIN = G_MAX_PARTICLE_NUM / G_BIN_CAPACITY;\n\tconstexpr std::size_t G_MAX_HALO_BLOCK\t = 4000;\n\n}// namespace config\n\n}// namespace mn\n\n#endif" }, { "path": "Projects/MGSP/utility_funcs.hpp", "content": "#ifndef UTILITY_FUNCS_HPP\n#define UTILITY_FUNCS_HPP\n#include \"settings.h\"\n\nnamespace mn {\n\n//TODO: Maybe create parameters fopr some of this magic numbers\n//NOLINTBEGIN(readability-magic-numbers) Magic numbers are formula-specific\n/// assume p is already within kernel range [-1.5, 1.5]\nconstexpr vec3 bspline_weight(float p) {\n\tvec3 dw {0.0f, 0.0f, 0.0f};\n\tfloat d = p * config::G_DX_INV;///< normalized offset\n\tdw[0]\t= 0.5f * (1.5f - d) * (1.5f - d);\n\td -= 1.0f;\n\tdw[1] = 0.75f - d * d;\n\td\t = 0.5f + d;\n\tdw[2] = 0.5f * d * d;\n\treturn dw;\n}\n\nconstexpr int dir_offset(ivec3 d) {\n\treturn (d[0] + 1) * 9 + (d[1] + 1) * 3 + d[2] + 1;\n}\nconstexpr void dir_components(int dir, ivec3& d) {\n\td[2] = (dir % 3) - 1;\n\td[1] = ((dir / 3) % 3) - 1;\n\td[0] = ((dir / 9) % 3) - 1;\n}\n//NOLINTEND(readability-magic-numbers) Magic numbers are formula-specific\n\n//NOLINTBEGIN(readability-magic-numbers) Magic numbers are formula-specific\nconstexpr float compute_dt(float max_vel, const float cur, const float next, const float dt_default) noexcept {\n\tif(next < cur) {\n\t\treturn 0.0f;\n\t}\n\n\tfloat dt = dt_default;\n\tif(max_vel > 0.0f) {\n\t\tmax_vel = config::G_DX * 0.3f / max_vel;\n\t\tif(max_vel < dt_default) {\n\t\t\tdt = max_vel;\n\t\t}\n\t}\n\n\tif(cur + dt >= next) {\n\t\tdt = next - cur;\n\t} else {\n\t\tmax_vel = (next - cur) * 0.51f;\n\t\tif(max_vel < dt) {\n\t\t\tdt = max_vel;\n\t\t}\n\t}\n\n\treturn dt;\n}\n//NOLINTEND(readability-magic-numbers) Magic numbers are formula-specific\n\n}// namespace mn\n\n#endif" }, { "path": "Projects/TaichiScripts/gmpm.py", "content": "import taichi as ti\n\nti.init(arch=ti.cuda)\n# sim setup\ndt = 1e-4\ndim = 3\ndomain_size = 256\ndx, inv_dx = 1 / domain_size, float(domain_size)\n\nblock_size = 4\nblock_num = domain_size / block_size\n\nparticle_num = 775196\nmax_particle_size = 64\n# material\np_vol, p_rho = (dx * 0.5)**3, 1\np_mass = p_vol * p_rho\nE, nu = 5e3, 0.2 # Young's modulus and Poisson's ratio\nmu_0, lambda_0 = E / (2 * (1 + nu)), E * nu / \\\n ((1+nu) * (1 - 2 * nu)) # Lame parameters\n\n# grid layout\ngrid_m = ti.var(dt=ti.f32)\ngrid_v = ti.Vector(3, dt=ti.f32)\n# particle layout\npar_pos = ti.Vector(3, dt=ti.f32)\npar_m = ti.var(ti.f32)\npar_v = ti.Vector(3, dt=ti.f32)\npar_F = ti.Matrix(3, 3, dt=ti.f32)\n# layout define\n@ti.layout\ndef buffers():\n ti.root.dense(ti.ijk, (block_num, block_num, block_num)).dense(ti.ijk,\n (block_size, block_size, block_size)).place(grid_m)\n for d in ti.static(range(3)):\n ti.root.dense(ti.ijk, (block_num, block_num, block_num)).dense(ti.ijk,\n (block_size, block_size, block_size)).place(grid_v(d))\n ti.root.dynamic(ti.i).place(par_pos(d))\n ti.root.dense(ti.ijk, (block_num, block_num, block_num)).dense(ti.ijk,\n (block_size, block_size, block_size)).dynamic(ti.i,\n max_particle_size).place(par_m)\n for d in ti.static(range(3)):\n ti.root.dense(ti.ijk, (block_num, block_num, block_num)).dense(ti.ijk,\n (block_size, block_size, block_size)).dynamic(ti.i,\n max_particle_size).place(par_v(d))\n for i, j in ti.static(ndrange(3, 3)):\n ti.root.dense(ti.ijk, (block_num, block_num, block_num)).dense(ti.ijk,\n (block_size, block_size, block_size)).dynamic(ti.i,\n max_particle_size).place(par_F(i, j))\n\n\n@ti.kernel\ndef initialize():\n for i in range(particle_num):\n par_pos[i] = ti.Vector([0, 0, 0])\n\n# with open(\"twodragons.bin\", 'rb') as f:\n" }, { "path": "README.md", "content": "# A Massively Parallel and Scalable Multi-GPU Material Point Method\n\n\n\n## Description\n\nThis is the opensource code for the SIGGRAPH 2020 paper:\n\n**A Massively Parallel and Scalable Multi-GPU Material Point Method** \n\n[page](https://sites.google.com/view/siggraph2020-multigpu)\\, [pdf](https://math.ucla.edu/~cffjiang/research/wang2020multigpu/wang2020multigpu.pdf)\\, [supp](https://math.ucla.edu/~cffjiang/research/wang2020multigpu/supp.pdf)\\, [video](https://vimeo.com/414136257)\n\nAuthors:\n[Xinlei Wang](https://github.com/littlemine)\\*, \n[Yuxing Qiu](https://yuxingqiu.github.io/)\\*, \n[Stuart R. Slattery](https://www.ornl.gov/staff-profile/stuart-r-slattery), \n[Yu Fang](http://squarefk.com/), \n[Minchen Li](https://www.seas.upenn.edu/~minchenl/), \n[Song-Chun Zhu](http://www.stat.ucla.edu/~sczhu/), \n[Yixin Zhu](https://yzhu.io/), \n[Min Tang](https://min-tang.github.io/home/), \n[Dinesh Manocha](https://www.cs.umd.edu/people/dmanocha)\n[Chenfanfu Jiang](https://math.ucla.edu/~cffjiang/)\n(* Equal contributions)\n\n

\n\n

\n\nHarnessing the power of modern multi-GPU architectures, we present a massively parallel simulation system based on the Material Point Method (MPM) for simulating physical behaviors of materials undergoing complex topological changes, self-collision, and large deformations. Our system makes three critical contributions. First, we introduce a new particle data structure that promotes coalesced memory access patterns on the GPU and eliminates the need for complex atomic operations on the memory hierarchy when writing particle data to the grid. Second, we propose a kernel fusion approach using a new Grid-to-Particles-to-Grid (G2P2G) scheme, which efficiently reduces GPU kernel launches, improves latency, and significantly reduces the amount of global memory needed to store particle data. Finally, we introduce optimized algorithmic designs that allow for efficient sparse grids in a shared memory context, enabling us to best utilize modern multi-GPU computational platforms for hybrid Lagrangian-Eulerian computational patterns. We demonstrate the effectiveness of our method with extensive benchmarks, evaluations, and dynamic simulations with elastoplasticity, granular media, and fluid dynamics. In comparisons against an open-source and heavily optimized CPU-based MPM codebase on an elastic sphere colliding scene with particle counts ranging from 5 to 40 million, our GPU MPM achieves over 100X per-time-step speedup on a workstation with an Intel 8086K CPU and a single Quadro P6000 GPU, exposing exciting possibilities for future MPM simulations in computer graphics and computational science. Moreover, compared to the state-of-the-art GPU MPM method, we not only achieve 2X acceleration on a single GPU but our kernel fusion strategy and Array-of-Structs-of-Array (AoSoA) data structure design also generalizes to multi-GPU systems. Our multi-GPU MPM exhibits near-perfect weak and strong scaling with 4 GPUs, enabling performant and large-scale simulations on a 1024x1024x1024 grid with close to 100 million particles with less than 4 minutes per frame on a single 4-GPU workstation and 134 million particles with less than 1 minute per frame on an 8-GPU workstation.\n\n\n\n\n## Compilation\nThis is a cross-platform C++/CUDA cmake project. The minimum version requirement of cmake is 3.15, yet the latest version is generally recommended. The required CUDA version is 10.2 or 11.\n\nCurrently, *supported OS* includes Windows 10 and Ubuntu (>=18.04), and *tested compilers* includes gcc8.4, msvc v142, clang-9 (includes msvc version). \n\n### Build\nRun the following command in the *root directory*. Note that adding \"--config Release\" to the last command is needed when compiling using msvc.\n```mkdir build\ncd build\ncmake ..\ncmake --build .\n```\n\nOr configure the project using the *CMake Tools* extension in *Visual Studio Code* (recommended).\n\n\n### Data\n\nCurrently, binary position data and the level-set (signed distance field) [data](https://github.com/littlemine/Data) are accepted as input files for particles. Uniformly sampling particles from analytic geometries is another viable way for the initialization of models.\n\n### Run Demos\nThe project provides the following GPU-based schemes for MPM:\n- **GMPM**: improved single-GPU pipeline\n- **MGSP**: static geometry (particle) partitioning multi-GPU pipeline\n\n\nGo to *Projects/\\*\\**, run the executable.\n\n## Code Usage\n> Use the codebase in another cmake c++ project.\n\nDirectly include the codebase as a submodule, and follow the examples in the *Projects*.\n\n> Develop upon the codebase.\n\nCreate a sub-folder in *Projects* with a cmake file at its root.\n\n## Bibtex\n\nPlease cite our paper if you use this code for your research: \n```\n@article{Wang2020multiGMPM,\n author = {Xinlei Wang* and Yuxing Qiu* and Stuart R. Slattery and Yu Fang and Minchen Li and Song-Chun Zhu and Yixin Zhu and Min Tang and Dinesh Manocha and Chenfanfu Jiang},\n title = {A Massively Parallel and Scalable Multi-GPU Material Point Method},\n journal = {ACM Transactions on Graphics},\n year = {2020},\n volume = {39},\n number = {4},\n articleno = {Article 30}\n}\n```\n\n## Credits\nThis project draws inspirations from [Taichi](https://github.com/taichi-dev/taichi), [GMPM](https://github.com/kuiwuchn/GPUMPM).\n\n### Acknowledgement\nWe thank [Yuanming Hu](http://taichi.graphics/me/) for useful discussions and proofreading, [Feng Gao](https://fen9.github.io/) for his help on configuring workstations. We appreciate Prof. [Chenfanfu Jiang](https://math.ucla.edu/~cffjiang/) and [Yuanming Hu](http://taichi.graphics/me/) for their insightful advice on the documentation.\n\n### Dependencies\nThe following libraries are adopted in our project development:\n\n- [cub](http://nvlabs.github.io/cub/) (now replaced by Thrust)\n- [fmt](https://fmt.dev/latest/index.html)\n\nFor particle data IO and generation, we use these two libraries in addition:\n\n- [partio](http://partio.us/)\n- [SDFGen](https://github.com/christopherbatty/SDFGen)\n\nDue to the C++ standard requirement (at most C++14) for compiling CUDA (10.2) code, we import these following libraries as well:\n\n- [function_ref](https://github.com/TartanLlama/function_ref)\n- [optional](https://github.com/TartanLlama/optional)\n- [variant](https://github.com/mpark/variant)\n" }, { "path": "docs/benchmark.rst", "content": "Benchmark\n==================\n\nSettings\n--------\nBenchmark settings of each project are set within its directory (e.g. *Projects/MGSP*) independently.\n\nGeneral setup\n`````````````\nMost configurations regarding the simulation are set in *settings.h*.\n\nData structure related setup:\n - **DOMAIN_BITS**: the resolution of the background grid in each dimension, e.g. 8 refers to a :math:`256 \\times 256 \\times 256` grid.\n - **MAX_PPC**: the maximum number of particles held within a cell.\n - **g_bin_capacity**: the number of particles in each particle bin.\n - **g_max_particle_num**: the maximum number of particles in each GPU.\n - **g_max_active_block**: the maximum number of blocks in each GPU. This affects the memory consumption of most important data structures (*particles*, *grid*, *partition*, etc).\n\nPhysical parameter setup:\n - **g_gravity**: the gravity constant.\n - **MODEL_PPC**: particle-per-cell for sampling particles from a SDF model. per-particle-volume is computed from this and the grid resolution.\n - **DENSITY**: the density constant of particles.\n - **get_material_type(int did) -> material**: the type of particles for each GPU. Assume each GPU handles only one category of particles.\n\nMulti-GPU related setup:\n - **g_device_num**: the number of GPUs used.\n - **get_domain(int did) -> domain**: the spatial partition domain for each GPU. It can be set time-dependently.\n\nAdditional material setup\n``````````````````````````\nIn *particle_buffer.cuh*, there are currently four types of particles supported. They are named *JFluid*, *FixedCorotated*, *Sand*, and *NACC*. \nWithin each **ParticleBuffer**, there are various material-dependent constant parameters that could be configured.\n\nInitial model setup\n``````````````````````````\nInitial particle models for all GPUs are set in the **init_models** function in *main.cu*.\n\nResults\n--------\n\nMulti-GPU scalability\n``````````````````````````\nThe following shows the `strong scalability `_ of our multi-GPU pipeline.\n\n.. image:: images/row_strong_speedup.jpg\n :width: 300px\n\n.. image:: images/row_strong_time.jpg\n :width: 300px\n\nThe following shows the `weak scalability `_ of our multi-GPU pipeline.\n\n.. image:: images/row_weak_speedup.jpg\n :width: 300px\n\n.. image:: images/row_weak_time.jpg\n :width: 300px" }, { "path": "docs/compilation.rst", "content": "Compilation\n=============\n\nThis is a cross-platform C++/CUDA cmake project. \nThe minimum version requirement of **CMake** is 3.15, although the latest version is generally recommended. \nThe recommended version of **CUDA** is 10.2.\n\nCurrently tested C++ compilers (as the host compiler for **NVCC**) on different platforms include:\n\n +----------+------------------+\n | platform | Compilers |\n +==========+==================+\n | Windows | msvc142, clang-9 |\n +----------+------------------+\n | Linux | gcc8.4, clang-9 |\n +----------+------------------+\n\nIn short, the supported compilers should support **C++14** standard and be in compliance with **NVCC**.\nSince the future releases of **CUDA** are officially excluded on Mac OS, and there is a more suitable candidate **Metal** developed by **Apple**, the **Mac OS** platform is not discussed.\n\nExternal Dependencies\n---------------------\nThese libraries are very helpful in developing this project and save a lot of efforts:\n\n- `CUB `_ provides state-of-the-art, reusable software components for every layer of the CUDA programming model including many parallel primitives and utilities.\n\n- `fmt `_ is an open-source formatting library for C++. \n\nThese libraries are used for particle data IO and initialization:\n\n- `partio `_ is an open source C++ library for reading, writing and manipulating a variety of standard particle formats (GEO, BGEO, PTC, PDB, PDA).\n\n- `SDFGen `_ is a simple commandline utility to generate grid-based signed distance field (level set) from triangle meshes, using code from Robert Bridson's website.\n\nBuild Commands\n-------------------\nRun the following command in the *root directory*.\n\n.. code-block:: bash\n\n mkdir build\n cd build\n cmake ..\n cmake --build . --config Release\n\nThe project can also be configured through other interfaces, e.g. using the *CMake Tools* extension in *Visual Studio Code* (recommended), in *Visual Studio Studio*, or in *CMake GUI*.\n" }, { "path": "docs/conf.py", "content": "# -*- coding: utf-8 -*-\n#\n# Mn documentation build configuration file, created by\n# sphinx-quickstart on Wed May 27 06:18:54 2020.\n#\n# This file is execfile()d with the current directory set to its\n# containing dir.\n#\n# Note that not all possible configuration values are present in this\n# autogenerated file.\n#\n# All configuration values have a default; values that are commented out\n# serve to show the default.\n\n# If extensions (or modules to document with autodoc) are in another directory,\n# add these directories to sys.path here. If the directory is relative to the\n# documentation root, use os.path.abspath to make it absolute, like shown here.\n#\n# import os\n# import sys\n# sys.path.insert(0, os.path.abspath('.'))\n\n\n# -- General configuration ------------------------------------------------\n\n# If your documentation needs a minimal Sphinx version, state it here.\n#\n# needs_sphinx = '1.0'\n\n# Add any Sphinx extension module names here, as strings. They can be\n# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom\n# ones.\nextensions = ['sphinx.ext.autodoc',\n 'sphinx.ext.todo',\n 'sphinx.ext.githubpages',\n 'sphinx.ext.mathjax',\n 'sphinx.ext.imgmath']\n\n# Add any paths that contain templates here, relative to this directory.\ntemplates_path = ['_templates']\n\n# The suffix(es) of source filenames.\n# You can specify multiple suffix as a list of string:\n#\n# source_suffix = ['.rst', '.md']\nsource_suffix = '.rst'\n\n# The master toctree document.\nmaster_doc = 'index'\n\n# General information about the project.\nproject = u'Claymore'\ncopyright = u'2020, Xinlei Wang, Yuxing Qiu, Stuart Slattery, Yu Fang, Minchen Li, Song-Chun Zhu, Yixin Zhu, Min Tang, Dinesh Manocha, Chenfanfu Jiang'\nauthor = u'Xinlei Wang, Yuxing Qiu, Stuart Slattery, Yu Fang, Minchen Li, Song-Chun Zhu, Yixin Zhu, Min Tang, Dinesh Manocha, Chenfanfu Jiang'\n\n# The version info for the project you're documenting, acts as replacement for\n# |version| and |release|, also used in various other places throughout the\n# built documents.\n#\n# The short X.Y version.\nversion = u'1.0'\n# The full version, including alpha/beta/rc tags.\nrelease = u'1.0'\n\n# The language for content autogenerated by Sphinx. Refer to documentation\n# for a list of supported languages.\n#\n# This is also used if you do content translation via gettext catalogs.\n# Usually you set \"language\" from the command line for these cases.\nlanguage = None\n\n# List of patterns, relative to source directory, that match files and\n# directories to ignore when looking for source files.\n# This patterns also effect to html_static_path and html_extra_path\nexclude_patterns = []\n\n# The name of the Pygments (syntax highlighting) style to use.\npygments_style = 'sphinx'\n\n# If true, `todo` and `todoList` produce output, else they produce nothing.\ntodo_include_todos = True\n\n\n# -- Options for HTML output ----------------------------------------------\n\n# The theme to use for HTML and HTML Help pages. See the documentation for\n# a list of builtin themes.\n#\nhtml_theme = 'sphinx_rtd_theme'\n\n# Theme options are theme-specific and customize the look and feel of a theme\n# further. For a list of options available for each theme, see the\n# documentation.\n#\n# html_theme_options = {}\n\n# Add any paths that contain custom static files (such as style sheets) here,\n# relative to this directory. They are copied after the builtin static files,\n# so a file named \"default.css\" will overwrite the builtin \"default.css\".\nhtml_static_path = ['_static']\n\n# Custom sidebar templates, must be a dictionary that maps document names\n# to template names.\n#\n# This is required for the alabaster theme\n# refs: http://alabaster.readthedocs.io/en/latest/installation.html#sidebars\nhtml_sidebars = {\n '**': [\n 'relations.html', # needs 'show_related': True theme option to display\n 'searchbox.html',\n ]\n}\n\n\n# -- Options for HTMLHelp output ------------------------------------------\n\n# Output file base name for HTML help builder.\nhtmlhelp_basename = 'claymore_doc'\n\n\n# -- Options for LaTeX output ---------------------------------------------\n\nlatex_elements = {\n # The paper size ('letterpaper' or 'a4paper').\n #\n # 'papersize': 'letterpaper',\n\n # The font size ('10pt', '11pt' or '12pt').\n #\n # 'pointsize': '10pt',\n\n # Additional stuff for the LaTeX preamble.\n #\n # 'preamble': '',\n\n # Latex figure (float) alignment\n #\n # 'figure_align': 'htbp',\n}\n\n# Grouping the document tree into LaTeX files. List of tuples\n# (source start file, target name, title,\n# author, documentclass [howto, manual, or own class]).\nlatex_documents = [\n (master_doc, 'Claymore.tex', u'Claymore Documentation',\n u'Xinlei Wang and Yuxing Qiu and Stuart R. Slattery and Yu Fang and Minchen Li and Song-Chun Zhu and Yixin Zhu and Min Tang and Dinesh Manocha and Chenfanfu Jiang', 'manual'),\n]\n\n\n# -- Options for manual page output ---------------------------------------\n\n# One entry per manual page. List of tuples\n# (source start file, name, description, authors, manual section).\nman_pages = [\n (master_doc, 'claymore', u'Claymore Documentation',\n [author], 1)\n]\n\n\n# -- Options for Texinfo output -------------------------------------------\n\n# Grouping the document tree into Texinfo files. List of tuples\n# (source start file, target name, title, author,\n# dir menu entry, description, category)\ntexinfo_documents = [\n (master_doc, 'Claymore', u'Claymore Documentation',\n author, 'Claymore', 'One line description of project.',\n 'Miscellaneous'),\n]\n" }, { "path": "docs/credits.rst", "content": "Acknowledgement\n===============\n\nWe thank Yuanming Hu for useful discussions and proofreading, Feng Gao for his help on configuring workstations. \n\nWe appreciate Prof. Chenfanfu Jiang and Yuanming Hu for their insightful advice on the documentation." }, { "path": "docs/datastructure.rst", "content": "Data Structure\n==============\nData structures in a MPM simulation usually need to model the particles, the grids and the mappings between them.\nCorrespondingly, we encapsulate these in *Partition*, *Particle Buffer* and *Grid Buffer*.\n\nPartition\n-----------\n**Partition** maintains the active elements, i.e. *block* in this context, and the mapping between block coordinates and linear indices through spatial hashing in the current timestep. \nBy *active element*, it means blocks that particles are assgined to, advect to or transfer to as shown below.\n\n.. image:: images/partition.jpg\n\nIt consists of an array to hold all the block coordinates (sparse information), hash tables for spatial hashing and particle buckets for holding particle indices grouped in blocks. \nIn multi-GPU cases, it additionally stores halo tags.\n\nParticle Buffer\n---------------\n**Particle Buffer** consists of particle bins from all the blocks that particles belong to. \nThis novel particle data structure is essentially in AoSoA layout similar to `Cabana `_.\n\n.. code-block:: cpp\n\n using f32_ = StructuralEntity;\n using Decorator = decorator;\n using ParticleBinDomain = aligned_domain;\n using particle_bin4_ = structural;\n\n using ParticleBufferDomain = compact_domain;\n using particle_buffer_ = structural;\n\nThe memory layout of each particle bin specified above is SoA with a total number of 4 attributes (arrays) for fluid particles and a length that is a multiple of 32 (warp size) for coalesced access.\nNote that the particle buffer is updated in a delayed fashion according to the particle index buckets in the previous substep.\nSince the particle buckets are known before *g2p2g*, writing to global memory is generally coalesced.\n\n.. image:: images/bin_structure.jpg\n\nGrid Buffer\n-----------\n**Grid Buffer** is composed of grid blocks that are currently visible to particles.\n\n.. code-block:: cpp\n\n using BlockDomain = compact_domain;\n using grid_block_ = structural;\n\n using GridBufferDomain = compact_domain;\n using grid_buffer_ = structural;\n\nThis is the same GPU-tailored SPGrid variant for grid structure used in an earlier `GPU implementation of MPM `_.\n\n.. note::\n For *particle buffer* and *grid buffer*, we store them in the device-local memory. If replaced with the virtual memory (*unified virtual memory* in CUDA), \n then the *ParticleBufferDomain* and *GridBufferDomain* could be replaced with *compact_domain* for a more straightforward access through block coordinates.\n However, we encountered unidentified issues utilizing the *unified virtual memory* on Window 10, and the difference between the two resulting performances is trivial.\n Thus we choose the former scheme which is relatively more robust and controllable." }, { "path": "docs/index.rst", "content": "Claymore Documentation\n==============================\n\n.. toctree::\n :caption: Overview\n :maxdepth: 3\n\n overview\n compilation\n\n.. toctree::\n :caption: Infrastructure\n :maxdepth: 3\n\n philosophy\n structural\n sparsity\n system\n usage\n\n.. toctree::\n :caption: GPU MPM\n :maxdepth: 3\n\n pipeline\n datastructure\n multigmpm\n benchmark\n\n.. toctree::\n :caption: About\n :maxdepth: 3\n\n credits" }, { "path": "docs/multigmpm.rst", "content": "Multi-GPU Design\n================\n\nReduce Memory Overhead\n----------------------\nTo extend from using a single GPU to running on multi-GPUs, we divide the whole simulation domain into partitions (maintained through a list of activated blocks covering\nall particles) according to the number of devices and assign one partition to one GPU device. \nAn efficient utilization of multi-GPUs for MPM needs to consider the following tasks:\n\n- **Halo Block Tagging**: tag the blocks that overlap partitions on other devices (i.e., the halo blocks).\n- **Halo Block Merging**: share block data in the halo region with other devices after executing the G2P2G kernel, for grid reduction and/or particle migration depending on partitioning strategies.\n\nThe latency of the memory transfer among GPU devices (required by the above tasks) relies highly on the underneath hardware setup. In most\nconsumer-level machines, multi-GPU devices are connected via the\nslow PCI-Express x16 Gen 3, which may lead to high communication latency. Fortunately, nearly all CUDA devices with compute capability of 1.1 or higher can concurrently perform the memory\ncopies and computing kernels. \nTherefore, it is viable and critical to hide the latency by overlapping data transfers with computations for a better performance scalability on multi-GPUs.\n\n.. image:: images/masking.jpg\n\nPartitioning Methods\n--------------------\nDepending on the dynamics of the simulation, the same partitioning scheme could result in drastically different performances on various scenes. \nTherefore we introduce detailed designs of two MPM-tailored variations of the most widely adopted partitioning methods, \ni.e. the *static geometric (particle) partitioning method* and the *static spatial partitioning method*.\n" }, { "path": "docs/overview.rst", "content": "Overview\n=============\n\nThis is the opensource code **Claymore** for the SIGGRAPH 2020 paper:\n\n**A Massively Parallel and Scalable Multi-GPU Material Point Method** \n\n`page `_, \n`pdf `_, \n`supp `_, \n`video `_\n\nAuthors: \n`Xinlei Wang\\* `_,\n`Yuxing Qiu\\* `_,\n`Stuart R. Slattery `_, \n`Yu Fang `_, \n`Minchen Li `_, \n`Song-Chun Zhu `_, \n`Yixin Zhu `_, \n`Min Tang `_, \n`Dinesh Manocha `_,\n`Chenfanfu Jiang `_\n(* Equal contributions)\n\nIntroduction\n------------\n\nHarnessing the power of modern multi-GPU architectures, we present a massively parallel simulation system based on the Material Point Method (MPM) for simulating physical behaviors of materials undergoing complex topological changes, self-collision, and large deformations. \nOur system makes three critical contributions:\n\n- Introduce a new particle data structure that promotes coalesced memory access patterns on the GPU and eliminates the need for complex atomic operations on the memory hierarchy when writing particle data to the grid. \n- Propose a kernel fusion approach using a new Grid-to-Particles-to-Grid (G2P2G) scheme, which efficiently reduces GPU kernel launches, improves latency, and significantly reduces the amount of global memory needed to store particle data. \n- Introduce optimized algorithmic designs that allow for efficient sparse grids in a shared memory context, enabling us to best utilize modern multi-GPU computational platforms for hybrid Lagrangian-Eulerian computational patterns. \n\nWe demonstrate the effectiveness of our method with extensive benchmarks, evaluations, and dynamic simulations with elastoplasticity, granular media, and fluid dynamics. In comparisons against an open-source and heavily optimized CPU-based MPM codebase on an elastic sphere colliding scene with particle counts ranging from 5 to 40 million, our GPU MPM achieves over 100X per-time-step speedup on a workstation with an Intel 8086K CPU and a single Quadro P6000 GPU, exposing exciting possibilities for future MPM simulations in computer graphics and computational science. \n\nMoreover, compared to the state-of-the-art GPU MPM method, we not only achieve 2X acceleration on a single GPU but our kernel fusion strategy and Array-of-Structs-of-Array (AoSoA) data structure design also generalizes to multi-GPU systems. \nOur multi-GPU MPM exhibits near-perfect weak and strong scaling with 4 GPUs, enabling performant and large-scale simulations on a 1024x1024x1024 grid with close to 100 million particles with less than 4 minutes per frame on a single 4-GPU workstation and 134 million particles with less than 1 minute per frame on an 8-GPU workstation.\n\nGallery\n------------\n\n.. image:: images/examples.jpg\n\nBibtex\n------\n\nPlease cite our paper if you use this code for your research: \n\n.. code-block:: none\n\n @article{Wang2020multiGMPM, \n author = {Xinlei Wang* and Yuxing Qiu* and Stuart R. Slattery and Yu Fang and Minchen Li and Song-Chun Zhu and Yixin Zhu and Min Tang and Dinesh Manocha and Chenfanfu Jiang},\n title = {A Massively Parallel and Scalable Multi-GPU Material Point Method},\n journal = {ACM Transactions on Graphics},\n year = {2020},\n volume = {39},\n number = {4},\n articleno = {Article 30}\n }\n" }, { "path": "docs/philosophy.rst", "content": "Design Philosophy\n=================\n\nData-Oriented Design\n--------------------\nDue to the increased overhead of memory over compute operations, \n**data-oriented design** philosophy has been widely adopted in software design. \nIt focuses on the data layout that is efficient for certain patterns of memory access. \nUsually, the optimization is achieved through better utilization of caches.\n\nHere are some of the most popular libraries providing efficient data structures.\n\n- `OpenVDB `_: OpenVDB is an open source C++ library comprising a novel hierarchical data structure and a large suite of tools for the efficient storage and manipulation of sparse volumetric data discretized on three-dimensional grids.\n- `SPGrid `_: SPGrid is a new data structure for compact storage and efficient stream processing of sparsely populated uniform Cartesian grids. It leverages the extensive hardware acceleration mechanisms inherent in the x86 Virtual Memory Management system to deliver sequential and stencil access bandwidth comparable to dense uniform grids.\n- `Cabana `_: As a generalization of SoA (Struct-of-Arrays) and AoS (Array-of-Structs) layouts, AoSoA (Array-of-Structs-of-Arrays), which is adopted by **Cabana**, appears to be a robust choice for both `CPU `_ and `GPU `_\n\nZero-Overhead Principle \n-----------------------\nBy C++ committee, the zero-overhead principle states that: What you don’t use, you don’t pay for (in time or space) and further: What you do use, you couldn’t hand code any better. \nAs Bjarne Stroustrup points out, it requires programming techniques, language features, and implementations to achieve such a zero-overhead abstraction.\nIn C++ language, designing an almost zero-overhead abstraction is sophisticated and difficult. \nBut it is worth working towards this goal. \nMeanwhile, such abstractions must provide more benefit than cost.\n\nDespite all the differences in the interpretations of *cost* (See `Chandler Carruth's talk `_), it is of great importance to reduce both the runtime cost as well as the build time cost (especially for C++). \nSometimes there even has to be a trade-off.\nSo we adopt the following practices in our codebase:\n\n- Use constexpr if feasible\n- Avoid recursive template instantiations\n- Encapsulate reusable units into precompiled libraries\n- ...\n" }, { "path": "docs/pipeline.rst", "content": "Simulator Pipeline\n==================\n\nOur MPM simulator adopts the explicit time-integration scheme. \n\nThe conventional MPM pipeline looks like:\n\n- **Particles-to-Grid (P2G)**. Transfer mass and momentum from particles to grid nodes: :math:`\\{m_p, m_p v_p^n\\} \\rightarrow \\{m_i, m_i v_i^n\\}`\n- **Grid Update**. Update grid velocities with either explicit or implicit time integration: :math:`v_i^{n} \\rightarrow v_i^{n+1}`\n- **Grid-to-Particles (G2P) and Particle Advection**. Transfer velocities from grid nodes to particles, evolve particle strains, and project particle deformation gradients for plasticity (if any). Update the particle positions with their new velocities: :math:`\\{v_i^{n+1}\\} \\rightarrow \\{v_p^{n+1}, F_p^{n+1}\\}`, :math:`\\{p_p^{n}, v_p^{n+1}\\} \\rightarrow \\{p_p^{n+1}\\}`\n- **Partition Update**. Maintain the sparse data structure topology by updating the active-block array and the mapping from block coordinates to array indices. \n\nWe propose a novel pipeline with a fused **G2P2G** kernel as a substitute for the original **P2G** and **G2P**. It allows less memory footprint for each particle (although in total doubled due to double-buffering required by G2P2G) and a better performance in general.\n\n.. image:: images/pipeline.jpg\n" }, { "path": "docs/sparsity.rst", "content": "Sparse Data Structures\n======================\n\nIn many graphics applications, e.g. ray tracing, collision detection, neighborhood search, etc., there exists a large amount of queries upon spatial data structures, \nand the involved volumetric data is often spatially sparse. Dedicated data structures like `OpenVDB `_ \nand `SPGrid `_ are introduced to provide efficient access to sparse data for specific operations.\nHowever, there is no best universal data structure for different types of sparsity and access patterns. \n\nThrough the previous **Hierarchy Composition** interface, we can compose and define sparse data structures very easily \nin order to experiment and identify an appropriate candidate for our need. \nIn our experiences, the sparse data structures can be categorized in terms of their underlying memory resource.\n\n- **Utilizing Virtual Memory**: rely on the virtual memory support from the underlying OS, driver and hardware.\n- **Manually Managing Memory**: manually maintain the sparse data, sometimes including a mapping from the discrete identifiers (e.g. spatial coordinates) to a contiguous sequence of indices.\n\nThen, providing allocators of specific memory resources to the **Structural Instance**, we complete defining the variable (instance), \nthe internal structure of which is specified by the **Structural Node**. Here we illustrate two common key aspects.\n\nAllocation\n----------\n\nUtilizing Virtual Memory\n````````````````````````\nThe automatic management of the virtual memory can help relieve the burden of manual maintenance. By avoiding frequent page-faults, \nthe access to the virtual memory can be as efficient as the heap or global memory (CUDA).\n\nDepending on the location of the memory we want to allocate for the instance, the allocation APIs are different.\n\nAllocation On Host\n''''''''''''''''''\n- Windows\n\n.. code-block:: cpp\n\n void* ptr = VirtualAlloc(nullptr, totalBytes, MEM_RESERVE, PAGE_READWRITE);\n\n- Linux\n\n.. code-block:: cpp\n\n void* ptr = mmap(nullptr, totalBytes, PROT_READ | PROT_WRITE, MAP_PRIVATE | MAP_ANONYMOUS | MAP_NORESERVE, -1, 0);\n\nAllocation On Device (CUDA)\n'''''''''''''''''''''''''''\n.. code-block:: cpp\n\n void* ptr;\n cudaMallocManaged((void **)&ptr, totalBytes);\n\nManually Managing Memory\n````````````````````````\nThe above method heavily relies on the support from the driver, and the granularity of the data unit should be on the same level as a page in the virtual memory system.\nTherefore it is often a more robust choice to manually manage the memory.\n\nAllocation On Host\n''''''''''''''''''\n.. code-block:: cpp\n\n void* ptr = (void *)malloc(totalBytes);\n\nAllocation On Device (CUDA)\n'''''''''''''''''''''''''''\n.. code-block:: cpp\n\n void* ptr;\n cudaMalloc((void **)&ptr, totalBytes);\n\nModeling Sparsity\n-----------------\nThe underlying memory resource intended for the sparse data structure largely influences the design of the data structure itself.\nHere we discuss multiple definitions of the *SPGrid-variants* using different strategies.\n\nUtilizing Virtual Memory\n````````````````````````\nThe virtual memory system can save the efforts of modeling the sparsity information. Simply defining the grid like a dense grid is sufficient.\n\n.. code-block:: cpp\n\n // domain\n using BlockDomain = domain;\n using GridDomain = domain;\n // decorator\n using DefaultDecorator = decorator;\n // structural node\n using grid_block_ = structural;\n using grid_ = structural;\n\n\nManually Managing Memory\n````````````````````````\nWhen adopting this strategy, the programmer should additionally maintain the mapping from spatial block coordinates to a contiguous sequence of indices.\nUsually we store this mapping through a (spatial) hash table or a lookup table. \nAnd the resulting data structure for the *SPGrid-variant* essentially becomes an array of grid blocks.\n\n.. code-block:: cpp\n\n using GridBufferDomain = domain;\n using grid_buffer_ = structural;\n\n" }, { "path": "docs/structural.rst", "content": "Hierarchy Composition\n=====================\n\nMotivation\n----------\nFollowing the principle **Data-Oriented Design**, `Yuanming Hu `_ introduces a high-performance programming language, `Taichi `_, wherein dedicated data structures can be developed by assembling components of different properties in static hierarchies.\nTaichi provides a powerful and easy-to-use toolchain for developing a wide range of high-performance applications. It implements an abstraction to define multi-level spatial data structures and kernel functions through a user-friendly python front-end and a robust LLVM back-end that automatically handles memory, manages executions, and deploys to CPU or GPU.\n\nLarge-scale simulations are spatially sparse in general, which pose great challenges to develop efficient data structures for specific spatial queries. \nIn MPM simulations, such queries involves grids in the Eulerian domain and particles in the Lagrangian domain.\nWe intend to exploit the aforementioned utility from Taichi for designing data structures. Due to the current lack of support of fully using Taichi in a C++ front-end, \na substitute is provided in native CUDA/C++ environment, which is implemented by C++ template meta-programming. \nPlease refer to our `tech doc `_ or read the following sections for more details.\n\n\nComponents\n----------\nThe entire infrastructure consists of the four major components: *Domain*, *Decorator*, *Structural Node*, and *Structural Instance*. For more details, please refer to *Library/MnBase/Object* in the opensourced code.\n\nDomain\n``````````````````````````\n**Domain** describes the range for the index of a data structure. It maps from multi-dimensional coordinates to a 1D memory span.\n\n.. code-block:: cpp\n\n template\n struct domain {\n template\n static constexpr Tn offset(Indices&&... indices);\n };\n\nDecorator\n``````````````````````````\n**Decorator** describes the auxiliary and detailed properties regarding the data structure it decorates.\n\n.. code-block:: cpp\n\n enum class structural_allocation_policy : std::size_t {\n full_allocation = 0,\n on_demand = 1,\n ...\n };\n enum class structural_padding_policy : std::size_t {\n compact = 0,\n align = 1,\n ...\n };\n enum class attrib_layout : std::size_t {\n aos = 0,\n soa = 1,\n ...\n };\n template \n struct decorator {\n static constexpr auto alloc_policy = alloc_policy_;\n static constexpr auto padding_policy = padding_policy_;\n static constexpr auto layout = layout_;\n };\n\nStructural Node\n``````````````````````````\n**Structural Nodes** with particular properties is formed in a hierarchy to compose a multi-level data structure.\nCurrently, we support three types of structural nodes (i.e., hash, dense, and dynamic). We are planning to support tree in future releases.\n\n.. code-block:: cpp\n\n enum class structural_type : std::size_t {\n /// leaf\n sentinel = 0,\n entity = 1,\n /// trunk\n hash = 2,\n dense = 3,\n dynamic = 4,\n ...\n };\n\nNo matter what the internal relationship of elements is within a structure (either contiguous- or node-based), \nwe assume there is at least one contiguous chunk of physical memory to store the data;\nthe size is a multiple of the extent of the Domain and the total size of all the attributes of an element (might be padded for alignment).\n\n.. code-block:: cpp\n\n /// attribute index of a structural node\n using attrib_index = placeholder::placeholder_type;\n\n /// traits of structural nodes\n template \n struct structural_traits {\n using attribs = type_seq;\n using self =\n structural;\n template \n using value_type = ...;\n static constexpr auto attrib_count = sizeof...(Structurals);\n static constexpr std::size_t element_size = ...;\n static constexpr std::size_t element_storage_size = ...;\n /// for allocation\n static constexpr std::size_t size = domain::extent * element_storage_size;\n\n template struct accessor {\n static constexpr uintptr_t element_stride_in_bytes = ...;\n static constexpr uintptr_t attrib_base_offset = ...;\n template \n static constexpr uintptr_t coord_offset(Indices &&... is) {\n return attrib_base_offset + Domain::offset(std::forward(is)...) * element_stride_in_bytes;\n }\n template \n static constexpr uintptr_t linear_offset(Index &&i) {\n return attrib_base_offset + std::forward(i) * element_stride_in_bytes;\n }\n };\n\n // manage memory\n template void allocate_handle(Allocator allocator) {\n if (self::size != 0)\n _handle.ptr = allocator.allocate(self::size);\n else\n _handle.ptr = nullptr;\n }\n template void deallocate(Allocator allocator) {\n allocator.deallocate(_handle.ptr, self::size);\n _handle.ptr = nullptr;\n }\n // access value\n template , typename... Indices>\n constexpr auto &val(std::integral_constant, Indices &&... indices) {\n return *reinterpret_cast(_handle.ptrval + accessor::coord_offset(std::forward(indices)...));\n }\n template , typename Index>\n constexpr auto &val_1d(std::integral_constant,\n Index &&index) {\n return *reinterpret_cast(\n _handle.ptrval +\n accessor::linear_offset(std::forward(index)));\n }\n /// data member\n MemResource _handle;\n };\n /// specializations of different types of structural nodes\n template \n struct structural : structural_traits {...};\n\nWe also define two special types of *Structural Nodes*, the root node and the leaf node, to form the hierarchy.\n\n.. code-block:: cpp\n\n /// special structural node\n template struct root_instance;\n template struct structural_entity;\n\nStructural Instance\n``````````````````````````\nA variable defined by the above **Structural Node** is an **Structural Instance** spawned given an allocator at the run-time. \nThe instance is customizable (e.g. accessing the parent node requires additional data) as it is assembled from selected data components.\n\n.. code-block:: cpp\n\n enum class structural_component_index : std::size_t {\n default_handle = 0,\n parent_scope_handle = 1,\n ...\n };\n\n template \n struct structural_instance_component;\n\n /// specializations for each data component\n template \n struct structural_instance_component {...};\n\nBesides the data components, the **Structural Instance** also inherits from the **Structural Node** that specifies the properties of itself.\n\n\n.. code-block:: cpp\n\n /// traits of structural instance, inherit from structural node\n template \n struct structural_instance_traits\n : parent_instance::attribs::template type<(std::size_t)AttribNo> {\n using self = typename parent_instance::attribs::type<(std::size_t)AttribNo>;\n using parent_indexer = typename parent_instance::domain::index;\n using self_indexer = typename self::domain::index;\n };\n\n /// structural instance, inherit from all data components and its traits (which is derived from structural node)\n template \n struct structural_instance;\n template \n struct structural_instance>\n : structural_instance_traits,\n structural_instance_component(Cs)>... {\n using traits = structural_instance_traits;\n using component_seq = std::integer_sequence;\n using self_instance =\n structural_instance;\n template \n using accessor = typename traits::template accessor;\n\n // hierarchy traverse\n template \n constexpr auto chfull(std::integral_constant,\n Indices &&... indices) const {\n ...\n }\n template \n constexpr auto ch(std::integral_constant,\n Indices &&... indices) const {\n ...\n }\n template \n constexpr auto chptr(std::integral_constant,\n Indices &&... indices) const {\n ...\n }\n };\n\nUsage\n----------\nHere, we showcase the usages of the above interface by providing an example of **SPGrid**.\n\nBasic Definitions\n``````````````````````````\nTo simplify the usage, we define certain types and variables that are frequently used.\n\n.. code-block:: cpp\n\n /// leaf node\n using empty_ = structural_entity;\n using i32_ = structural_entity;\n using f32_ = structural_entity;\n\n /// attribute index\n namespace placeholder {\n using placeholder_type = unsigned;\n constexpr auto _0 = std::integral_constant{};\n constexpr auto _1 = std::integral_constant{};\n ...\n }\n\n /// default data components for constructing instances\n using orphan_signature = std::integer_sequence(structural_component_index::default_handle)>;\n\nStructural Node Definition\n``````````````````````````\nThe following code defines the **SPGrid** used in our pipeline.\n\n.. code-block:: cpp\n\n // domain\n using BlockDomain = domain;\n using GridBufferDomain = domain;\n // decorator\n using DefaultDecorator = decorator;\n // structural node\n using grid_block_ = structural;\n using grid_buffer_ = structural;\n\n\nCreate Structural Instance\n``````````````````````````\nAfter defining the internal structure, it still requires an allocator and the list of data components to get the instance.\n\n.. code-block:: cpp\n\n template \n using Instance = structural_instance, (attrib_index)0, Signature>;\n\n template \n constexpr auto spawn(Allocator allocator) {\n auto ret = Instance{};\n ret.allocate_handle(allocator);\n return ret;\n }\n\n auto allocator = ...;\n auto spgrid = spawn(allocator);\n\nAccess Interface\n``````````````````````````\nGenerally, we need to provide both the attribute and child index to access a child of such an instance.\n\n.. code-block:: cpp\n\n /// acquire blockno-th grid block\n auto grid_block = spgrid.ch(_0, blockno);\n /// access cidib-th cell within this block\n grid_block.val_1d(_0, cidib); // access 0-th channel (mass)\n /// access cell within by coordinates\n grid_block.val(_1, cx, cy, cz); // access 1-th channel (velocity x)\n\nInternal Layout\n---------------\nTo gain a better insight into the internal layout, we here give another example.\n\n.. image:: images/structural.jpg\n.. code-block:: cpp\n\n using Attrib0 = structural_entity;\n using Attrib1 = structural_entity;\n using DecoratorA = decorator<\n structural_allocation_policy::full_allocation, \n structural_padding_policy::align, \n attrib_layout:aos>;\n using DecoratorB = decorator<\n structural_allocation_policy::full_allocation, \n structural_padding_policy::align, \n attrib_layout:soa>;\n using StructuralA = structural, Attr0, Attr1>;\n using StructuralB = Structural, Attr0, Attr1>;\n\n :caption: Two *structural nodes* are specified with different *decorators*. The arrows connecting all elements indicate the ascending order in a contiguous chunk of memory. The *structural node* can be used as an attribute of another *structural node* to form a multi-level hierarchy. Elements displayed in the grid view are accessed by an attribute index (marked with different colors) and a coordinate within its domain. Note that the memory size of each *structural* is padded to the next power of 2 due to the alignment decoration.\n\n" }, { "path": "docs/system.rst", "content": "System\n======\n\nTo conveniently reuse the code required for a specific type of tasks, we build a precompiled and customized library, i.e. **system**.\nIt is essentially a **Singleton** class which can be selectively included and utilized by projects.\n\nCUDA\n----\n\n**CUDA** system provides CUDA related utilities, including \n- setting up the GPU devices, constructing necessary resources and enabling certain features.\n- temporary memory pools of various memory type for intermediate computations.\n- context handles, each corresponding to one GPU, through which programmers launch kernels, synchronize among streams, manage memory, etc.\n\nAlso, a few helper functions that can be called on the host side or the device side are also included.\n\nIO\n----\n\n**IO** system currently only provide what is necessary for the MPM project, e.g. reading geometry data and outputting generated particle data asynchronously." }, { "path": "docs/usage.rst", "content": "Usage\n=====\n\n**Q**: Use the codebase in another cmake c++ project.\n\n**A**: Directly include the codebase as a submodule, and follow the examples in the *Projects*.\n\n**Q**: Develop upon the codebase.\n\n**A**: Create a sub-folder in *Projects* with a cmake file at its root." }, { "path": "project_info.in", "content": "set(project_version 0.0.0)\nset(project_description \"gpu-based mpm simulator\")\n" } ]